Intent-based scheduling via digital personal assistant

ABSTRACT

Techniques are described herein that are capable of performing intent-based scheduling via a digital personal assistant. For instance, an intent of user(s) to perform an action (a.k.a. activity) may be used to schedule time (e.g., on a calendar of at least one of the user(s)) in which the action is to be performed. Examples of performing an action include but are not limited to having a meeting, working on a project, participating in a social event, exercising, and reading.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application claims the benefit of U.S. Provisional Application No.62/314,966, filed Mar. 29, 2016 and entitled “Extensibility forContext-Aware Digital Personal Assistant,” the entirety of which isincorporated by reference herein.

BACKGROUND

It has become relatively common for devices, such as laptop computers,tablet computers, personal digital assistants (PDAs), and cell phones,to have digital personal assistant functionality. A digital personalassistant is a representation of an entity that interacts with a user ofa device. For instance, the digital personal assistant may answerquestions that are asked by the user or perform tasks based oninstructions from the user. One example of a digital personal assistantis Siri®, which was initially developed by Siri, Inc. and has since beenfurther developed and maintained by Apple Inc. Another example of adigital personal assistant is Cortana®, which is developed andmaintained by Microsoft Corporation. Although a digital personalassistant typically is able to communicate with a user of a device,functionality of conventional digital personal assistants often islimited to reacting to specific requests from the user.

SUMMARY

Various approaches are described herein for, among other things,performing intent-based scheduling via a digital personal assistant. Forinstance, an intent of user(s) to perform an action (a.k.a. activity)may be used to schedule time (e.g., on a calendar of at least one of theuser(s)) in which the action is to be performed. Examples of performingan action include but are not limited to having a meeting, working on aproject, participating in a social event, exercising, and reading.

In a first example approach, communication(s) from a first user areanalyzed (e.g., programmatically analyzed or processed) to identify afirst communication from the first user that indicates that the firstuser has an intent to have a first meeting between at least the firstuser and second user(s). Communication(s) from the second user(s) areanalyzed to identify second communication(s) from the second user(s)that are in response to the first communication and that indicate thatthe second user(s) have the intent to have the first meeting. A digitalpersonal assistant is caused (e.g., programmatically configured) toautomatically propose and/or automatically schedule a time to have thefirst meeting between at least the first user and the second user(s)based at least in part on the first communication and the secondcommunication(s) indicating that the first user and the second user(s)have the intent to have the first meeting.

In a second example approach, interactions among users are identified.Tools that are used to facilitate the interactions are identified. Anintent to have a meeting between the users is inferred. A designatedtool is automatically selected to establish communication for themeeting based at least in part on the designated tool being used morethan other tools to facilitate the interactions. A digital personalassistant is caused to automatically schedule the meeting and/orautomatically propose to schedule the meeting based at least in part onan inference of the intent to have the meeting.

In a third example approach, communication(s) from a first user areanalyzed to infer from at least a first communication that the firstuser has an intent to perform an activity. A digital personal assistantis caused to automatically schedule a designated time on a visualrepresentation of a calendar of the first user to perform the activity,including causing the digital personal assistant to automatically updatethe visual representation of the calendar to include a visualrepresentation of the activity that is configured to indicate that thedesignated time is scheduled to perform the activity, based at least inpart on an inference from at least the first communication that thefirst user has the intent to perform the activity.

In a fourth example approach, instances of an action that are performedby a user at respective historical time instances are analyzed toidentify a trend with regard to the instances of the action. A digitalpersonal assistant is caused to automatically schedule a designated timefor the user to perform a future instance of the action in accordancewith the trend, including causing the digital personal assistant toconfigure a visual representation of a calendar of the user to indicatethat availability of the user at the designated time is tentative orbooked.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used to limit the scope of the claimed subject matter. Moreover, itis noted that the invention is not limited to the specific embodimentsdescribed in the Detailed Description and/or other sections of thisdocument. Such embodiments are presented herein for illustrativepurposes only. Additional embodiments will be apparent to personsskilled in the relevant art(s) based on the teachings contained herein.

BRIEF DESCRIPTION OF THE DRAWINGS/FIGURES

The accompanying drawings, which are incorporated herein and form partof the specification, illustrate embodiments of the present inventionand, together with the description, further serve to explain theprinciples involved and to enable a person skilled in the relevantart(s) to make and use the disclosed technologies.

FIG. 1 is a block diagram of an example intent-based scheduling systemin accordance with an embodiment.

FIGS. 2, 6-7, 9, and 11 depict flowcharts of example methods forperforming intent-based scheduling via a digital personal assistant inaccordance with embodiments.

FIGS. 3, 8, 10, and 12 are block diagrams of example computing systemsin accordance with embodiments.

FIG. 4 depicts a flowchart of an example method for causing a digitalpersonal assistant to automatically reschedule a meeting in accordancewith an embodiment.

FIG. 5 is a block diagram of an example implementation of causationlogic shown in FIGS. 3, 8, 10, and 12 in accordance with embodiments.

FIG. 13 depicts a flowchart of an example method for causing a digitalpersonal assistant to automatically reschedule a previously scheduledactivity in accordance with an embodiment.

FIG. 14 depicts an example computer in which embodiments may beimplemented.

The features and advantages of the disclosed technologies will becomemore apparent from the detailed description set forth below when takenin conjunction with the drawings, in which like reference charactersidentify corresponding elements throughout. In the drawings, likereference numbers generally indicate identical, functionally similar,and/or structurally similar elements. The drawing in which an elementfirst appears is indicated by the leftmost digit(s) in the correspondingreference number.

DETAILED DESCRIPTION I. Introduction

The following detailed description refers to the accompanying drawingsthat illustrate exemplary embodiments of the present invention. However,the scope of the present invention is not limited to these embodiments,but is instead defined by the appended claims. Thus, embodiments beyondthose shown in the accompanying drawings, such as modified versions ofthe illustrated embodiments, may nevertheless be encompassed by thepresent invention.

References in the specification to “one embodiment,” “an embodiment,”“an example embodiment,” or the like, indicate that the embodimentdescribed may include a particular feature, structure, orcharacteristic, but every embodiment may not necessarily include theparticular feature, structure, or characteristic. Moreover, such phrasesare not necessarily referring to the same embodiment. Furthermore, whena particular feature, structure, or characteristic is described inconnection with an embodiment, it is submitted that it is within theknowledge of one skilled in the relevant art(s) to implement suchfeature, structure, or characteristic in connection with otherembodiments whether or not explicitly described.

II. Example Embodiments

Example embodiments described herein are capable of performingintent-based scheduling via a digital personal assistant. For instance,an intent of user(s) to perform an action (a.k.a. activity) may be usedto propose and/or schedule time (e.g., on a calendar of at least one ofthe user(s)) in which the action is to be performed. Examples ofperforming an action include but are not limited to having a meeting,working on a project, participating in a social event, exercising, andreading.

Example techniques described herein have a variety of benefits ascompared to conventional techniques for managing a schedule of a user.For instance, the example techniques may be capable of automaticallyproposing and/or scheduling time in which to perform an activity basedat least in part on inferred intent of the user and/or other user(s),automatically updating a calendar to reflect an appointment or meetingfor performance of the activity, automatically managing conflicts withregard to the appointment or meeting (e.g., based on inferred relativeimportance of the conflicting activities), and automatically inferringattribute(s) of the appointment or meeting. Examples of an attributeinclude but are not limited to a location at which the appointment ormeeting is to occur, a communication channel to be used for theappointment or meeting, documentation to be used in preparation forand/or during the appointment or meeting, and people to be notifiedabout and/or invited to the appointment or meeting.

The example techniques may simplify a process for managing a schedule ofa user. The example techniques may reduce an amount of time and/orresources (e.g., processor, memory, network bandwidth) that are consumedto manage the schedule of the user. The example embodiments may increaseefficiency of a computing device that is used to manage the schedule ofthe user. The example techniques may increase user efficiency (e.g., byreducing a number of steps that a user takes to manage the schedule ofthe user). For instance, the example techniques described herein mayreduce (e.g., eliminate) a need for a user to manually add anappointment or meeting to a calendar and/or to manage conflicts (e.g.,temporal conflicts) associated with such appointment or meeting.

FIG. 1 is a block diagram of an example intent-based scheduling system100 in accordance with an embodiment. Generally speaking, intent-basedscheduling system 100 operates to provide information to users inresponse to requests (e.g., hypertext transfer protocol (HTTP) requests)that are received from the users. The information may include documents(e.g., Web pages, images, audio files, video files, etc.), output ofexecutables, and/or any other suitable type of information. Inaccordance with example embodiments described herein, intent-basedscheduling system 100 performs intent-based scheduling via a digitalpersonal assistant. For instance, a user may dread creating andscheduling activities (e.g., meetings), updating a calendar to reflectsuch activities and the availability of the user, gathering informationthat is needed for the activities, and so on. The user may desire todelegate such tasks to a digital personal assistant. Intent-basedscheduling logic 110 may infer (e.g., compute) an intent of the user toperform such tasks and cause (e.g., programmatically configure) thedigital personal assistant to automatically perform the tasks on behalfof the user and/or to automatically provide recommendations to the userregarding the same (e.g., a recommended time, location, communicationchannel, documentation, attendees, and so on). Intent-based schedulinglogic 110 may cause the digital personal assistant to enable the user tocreate an instruction to perform the task(s) automatically when the sameintent is inferred in the future.

Intent of a user may be inferred based on any of a variety of factors,including but not limited to content of communication(s) among users, abehavioral trend of the user (e.g., a trend of activities performed bythe user), and a location of the user. Examples of a communicationinclude but are not limited to a telephone call, an in-personconversation, a conversation via a software application (e.g., Skype®,developed and distributed originally by Skype Technologies S.A.R.L. andsubsequently by Microsoft Corporation; Whatsapp® Messenger, developedand distributed by WhatsApp Inc.; and Facebook® Messenger, developed anddistributed by Facebook, Inc.), a voice mail, an email, a text message,a short message service (SMS) message, and a social update.

Detail regarding techniques for performing intent-based scheduling via adigital personal assistant is provided in the following discussion.

As shown in FIG. 1, intent-based scheduling system 100 includes aplurality of user devices 102A-102M, a network 104, and a plurality ofservers 106A-106N. Communication among user devices 102A-102M andservers 106A-106N is carried out over network 104 using well-knownnetwork communication protocols. Network 104 may be a wide-area network(e.g., the Internet), a local area network (LAN), another type ofnetwork, or a combination thereof.

User devices 102A-102M are processing systems that are capable ofcommunicating with servers 106A-106N. An example of a processing systemis a system that includes at least one processor that is capable ofmanipulating data in accordance with a set of instructions. Forinstance, a processing system may be a computer, a personal digitalassistant, etc. User devices 102A-102M are configured to providerequests to servers 106A-106N for requesting information stored on (orotherwise accessible via) servers 106A-106N. For instance, a user mayinitiate a request for executing a computer program (e.g., anapplication) using a client (e.g., a Web browser, Web crawler, or othertype of client) deployed on a user device 102 that is owned by orotherwise accessible to the user. In accordance with some exampleembodiments, user devices 102A-102M are capable of accessing domains(e.g., Web sites) hosted by servers 106A-106N, so that user devices102A-102M may access information that is available via the domains. Suchdomain may include Web pages, which may be provided as hypertext markuplanguage (HTML) documents and objects (e.g., files) that are linkedtherein, for example.

Each of user devices 102A-102M may include any client-enabled system ordevice, including but not limited to a desktop computer, a laptopcomputer, a tablet computer, a wearable computer such as a smart watchor a head-mounted computer, a personal digital assistant, a cellulartelephone, or the like. It will be recognized that any one or more usersystems 102A-102M may communicate with any one or more servers106A-106N.

User devices 102A-102M are shown to include respective digital personalassistants 108A-108M. Digital personal assistants 108A-108M arerepresentations of respective entities that interact with users of userdevices 102A-102M. Each of the digital personal assistants 108A-108M maybe configured (e.g., controlled) to perform task(s) on behalf of theuser(s) of the respective user device and/or to propose performance ofthe task(s) when an intent to perform the task(s) is inferred. Forexample, first digital personal assistant 108A may be configured toautomatically propose and/or automatically schedule a time to perform afirst activity in response to an intent of user(s) of first user device102A to perform the first activity being inferred (e.g., fromcommunication(s) of the user(s) of first user device 102A). Seconddigital personal assistant 108B may be configured to automaticallypropose and/or automatically schedule a time to perform a secondactivity, which may be same as or different from the first activity, inresponse to an intent of user(s) of second user device 102B to performthe second activity being inferred (e.g., from communication(s) of theuser(s) of second user device 102A), and so on.

Servers 106A-106N are processing systems that are capable ofcommunicating with user devices 102A-102M. Servers 106A-106N areconfigured to execute computer programs that provide information tousers in response to receiving requests from the users. For example, theinformation may include documents (e.g., Web pages, images, audio files,video files, etc.), output of executables, or any other suitable type ofinformation. In accordance with some example embodiments, servers106A-106N are configured to host respective Web sites, so that the Websites are accessible to users of intent-based scheduling system 100.

First server(s) 106A is shown to include intent-based scheduling logic110 for illustrative purposes. Intent-based scheduling logic 110 isconfigured to implement digital personal assistants 108A-108M. Forexample, intent-based scheduling logic 110 may implement any one or moreof digital personal assistants 108A-108M to manage scheduling for users.

Some example functionality of intent-based scheduling logic 110 will nowbe described with reference to first digital personal assistant 108A forpurposes of illustration and is not intended to be limiting. It will berecognized that the functionality of intent-based scheduling logic 110described herein is applicable to any suitable digital personalassistant (e.g., any one or more of digital personal assistants108A-108M).

In a first example approach, intent-based scheduling logic 110 analyzes(e.g., programmatically analyzes or processes) communication(s) from afirst user to identify a first communication from the first user thatindicates that the first user has an intent to have a first meetingbetween at least the first user and second user(s). In one illustrationof this approach, the first user may say, “Let's meet tomorrow to reviewthis deck.” In accordance with this illustration, the first user'sstatement indicates that the first user has an intent to have a meetingwith one or more second users tomorrow.

In accordance with this approach, intent-based scheduling logic 110analyzes communication(s) from the second user(s) to identify secondcommunication(s) from the second user(s) that are in response to thefirst communication and that indicate that the second user(s) have theintent to have the first meeting. In the aforementioned illustration ofthis approach, a designated second user may say, “Sure, let's meet.” Inaccordance with this illustration, the designated second user'sstatement constitutes a response to the first user's statement andindicates that the designated second user has the intent to have themeeting.

In further accordance with this approach, intent-based scheduling logic110 causes (e.g., programmatically configures) a digital personalassistant to automatically propose and/or automatically schedule a timeto have the first meeting between at least the first user and the seconduser(s) based at least in part on the first communication and the secondcommunication(s) indicating that the first user and the second user(s)have the intent to have the first meeting. In the aforementionedillustration of this approach, assume that first user device 102Abelongs to or is otherwise accessible to the first user, and the Mthuser device 102M belongs to or is otherwise accessible to the seconduser. In accordance with this illustration, intent-based schedulinglogic 110 may cause at least first digital personal assistant 108Aand/or Mth digital personal assistant to automatically propose and/orschedule a time to have the meeting between at least the first user andthe designated second user. It should be mentioned that intent-basedscheduling logic 110 may cause any one or more of digital personalassistants 108A-108M that are associated with the second user(s) toautomatically propose and/or schedule the time to have the meetingbetween the first user and any one or more of the second user(s) (e.g.,based at least in part on the first user's statement and the designatedsecond user's statement indicating the intent to have the meeting).

In a second example approach, intent-based scheduling logic 110identifies interactions among users (e.g., users of any one or more ofuser devices 102A-102M). In one illustration of this approach, firstuser may have an in-person conversation with a second user, and thesecond user subsequently may have a telephone conference call with thirdand fourth users. In accordance with this illustration, intent-basedscheduling logic 110 may identify the in-person conversation between thefirst and second users and the telephone conference call between thesecond, third, and fourth users.

In accordance with this approach, intent-based scheduling logic 110identifies tools that are used to facilitate the interactions. In theaforementioned illustration of this approach, intent-based schedulinglogic 110 may identify the in-person engagement and the telephonenetwork as the tools that are used to facilitate the in-personconversation and the telephone conference call, respectively.

In further accordance with this approach, intent-based scheduling logic110 infers an intent to have a meeting between the users. In theaforementioned illustration of this approach, intent-based schedulinglogic 110 may infer that at least one of the first, second, third, andfourth users has an intent to have a meeting among the first, second,third, and fourth users. For instance, the intent may be inferred fromstatement(s) made during the in-person conversation and/or the telephoneconference call and/or a different conversation by one or more of thefirst, second, third, and fourth users.

In further accordance with this approach, intent-based scheduling logic110 automatically selects a designated tool to establish communicationfor the meeting based at least in part on the designated tool being usedmore than other tools to facilitate the interactions. In theaforementioned illustration of this approach, intent-based schedulinglogic 110 may automatically select in-person engagement as the tool toestablish communication for the meeting based on the first, second,third, and fourth users most often meeting in-person to discuss issues.

In further accordance with this approach, intent-based scheduling logic110 causes a digital personal assistant to automatically schedule themeeting and/or automatically propose to schedule the meeting based atleast in part on an inference of the intent to have the meeting. In theaforementioned illustration of this approach, intent-based schedulinglogic 110 may cause any of digital personal assistants 108A-108M thatare associated with the first, second, third, and/or fourth users toautomatically schedule the meeting and/or automatically propose toschedule the meeting to be in-person, though intent-based schedulinglogic 110 may provide (or offer to provide) a teleconference bridge incause any of the first, second, third, and fourth users are unable tomeet in-person.

In a third example approach, intent-based scheduling logic 110 analyzescommunication(s) from a first user to infer from at least a firstcommunication that the first user has an intent to perform an activity.In one illustration of this approach, first user may say, “I reallyshould hit the gym during lunch today.” In accordance with thisillustration, intent-based scheduling logic 110 may infer from the firstuser's statement that the first user has an intent to work-out at thegym during lunch.

In accordance with this approach, intent-based scheduling logic 110causes a digital personal assistant to automatically schedule adesignated time on a visual representation of a calendar of the firstuser to perform the activity, including causing the digital personalassistant to automatically update the visual representation of thecalendar to include a visual representation of the activity that isconfigured to indicate that the designated time is scheduled to performthe activity, based at least in part on an inference from at least thefirst communication that the first user has the intent to perform theactivity. In the aforementioned illustration of this approach, assumethat first user device 102A belongs to or is otherwise accessible to thefirst user. In accordance with this illustration, intent-basedscheduling logic 110 may determine (e.g., infer) that the first usertypically eats lunch at 1:30-2:15 pm. In accordance with thisillustration, intent-based scheduling logic 110 may cause digitalpersonal assistant 108A automatically schedule 1:30-2:15 pm on a visualrepresentation of the first user's calendar to work-out at the gym. Infurther accordance with this illustration, intent-based scheduling logic110 may cause digital personal assistant 108A to automatically updatethe visual representation of the first user's calendar to include avisual representation of the work-out (e.g., an appointment). In furtheraccordance with this illustration, the visual representation of thework-out may be configured to indicate that 1:30-2:15 pm is scheduled towork-out at the gym.

In a fourth example approach, intent-based scheduling logic 110 analyzesinstances of an action that are performed by a user (e.g., a user offirst user device 102A) at respective historical time instances toidentify a trend with regard to the instances of the action. In oneillustration of this approach, the user may watch a television series atthe 7:00 pm every Sunday. Intent-based scheduling logic 110 may analyzethe instances in which the user watches the television series todetermine a trend with regard to the user watching the televisionseries. In accordance with this illustration, intent-based schedulinglogic 110 may monitor the user's television watching habits to identifythe trend.

In accordance with this approach, intent-based scheduling logic 110causes a digital personal assistant to automatically schedule adesignated time for the user to perform a future instance of the actionin accordance with the trend, including causing the digital personalassistant to configure a visual representation of a calendar of the userto indicate that availability of the user at the designated time istentative or booked. In the aforementioned illustration of thisapproach, assume that first user device 102A belongs to or is otherwiseaccessible to the user. In accordance with this illustration,intent-based scheduling logic 110 may cause digital personal assistant108A to automatically schedule 7:00-7:30 pm next Sunday for the user towatch the television series in accordance with the trend. In furtheraccordance with this illustration, intent-based scheduling logic 110 maycause digital personal assistant 108A to configure a visualrepresentation of the user's calendar to indicate that availability ofthe user at 7:00-7:30 pm next Sunday is tentative or booked.

In some example embodiments, intent-based scheduling logic 110 gathersinformation about a user over time. In these embodiments, asintent-based scheduling logic 110 gathers the information over time, theaccuracy of inferences to perform activities and the appropriateness ofautomatically proposed and/or scheduled times for performing theactivities may be greater than the accuracy of previous inferences toperform activities and the appropriateness of times for performing theactivities that were previously automatically proposed and/or scheduled.For instance, intent-based scheduling logic 110 may develop a model ofthe user or a group to which the user belongs. Intent-based schedulinglogic 110 may develop and/or refine the model using online learning, forexample.

Intent-based scheduling logic 110 may be implemented in various ways toperform intent-based scheduling via a digital personal assistant,including being implemented in hardware, software, firmware, or anycombination thereof. For example, intent-based scheduling logic 110 maybe implemented as computer program code configured to be executed in oneor more processors. In another example, intent-based scheduling logic110 may be implemented as hardware logic/electrical circuitry. Forinstance, intent-based scheduling logic 110 may be implemented in afield-programmable gate array (FPGA), an application-specific integratedcircuit (ASIC), an application-specific standard product (ASSP), asystem-on-a-chip system (SoC), a complex programmable logic device(CPLD), etc. Each SoC may include an integrated circuit chip thatincludes one or more of a processor (e.g., a microcontroller,microprocessor, digital signal processor (DSP), etc.), memory, one ormore communication interfaces, and/or further circuits and/or embeddedfirmware to perform its functions.

Intent-based scheduling logic 110 is shown to be incorporated in firstserver(s) 106A for illustrative purposes and is not intended to belimiting. It will be recognized that intent-based scheduling logic 110(or any portion(s) thereof) may be incorporated in any one or more ofthe user systems 102A-102M. For example, client-side aspects ofintent-based scheduling logic 110 may be incorporated in one or more ofthe user systems 102A-102M, and server-side aspects of intent-basedscheduling logic 110 may be incorporated in first server(s) 106A. Inanother example, intent-based scheduling logic 110 may be distributedamong the user systems 102A-102M. In yet another example, intent-basedscheduling logic 110 may be incorporated in a single one of the usersystems 102A-102M. In another example, intent-based scheduling logic 110may be distributed among the server(s) 106A-106N. In still anotherexample, intent-based scheduling logic 110 may be incorporated in asingle one of the server(s) 106A-106N.

In some example embodiments, user(s) may interact with a digitalpersonal assistant via intent-based scheduling logic 110 using voicecommands, gesture commands, touch commands, and/or hover commands. Forexample, any one or more of the user devices 102A-102M may have amicrophone that is configured to detect voice commands. In anotherexample, any one or more of the user devices 102A-102M may have a camerathat is configured to detect gesture commands. In yet another example,any one or more of the user devices 102A-102M may have a touch screenthat is configured to detect touch commands and/or hover commands. Ahover command may include a hover gesture. A hover gesture can occurwithout a user physically touching the touch screen. Instead, the user'shand or portion thereof (e.g., one or more fingers) can be positioned ata spaced distance above the touch screen. The touch screen can detectthat the user's hand (or portion thereof) is proximate the touch screen,such as through capacitive sensing. Additionally, hand movement and/orfinger movement can be detected while the hand and/or finger(s) arehovering to expand the existing options for gesture input. Intent-basedscheduling logic 110 may infer an intent of the user based at least inpart on any of such voice, gesture, touch, and/or hover interactions.

Example techniques for performing intent-based scheduling via a digitalpersonal assistant are discussed in greater detail below with referenceto FIGS. 2-13.

FIG. 2 depicts a flowchart 200 of an example method for performingintent-based scheduling via a digital personal assistant in accordancewith an embodiment. Flowchart 200 may be performed by intent-basedscheduling logic 110 shown in FIG. 1, for example. For illustrativepurposes, flowchart 200 is described with respect to computing system300 shown in FIG. 3. Computing system 300 may include one or more ofuser systems 102A-102M, one or more of server(s) 106A-106N, or anycombination thereof, though the scope of the example embodiments is notlimited in this respect. Computing system 300 includes intent-basedscheduling logic 302, which is an example of intent-based schedulinglogic 110, according to an embodiment. As shown in FIG. 3, computingsystem 300 further includes a store 304 and a digital personal assistant306. Store 304 may be any suitable type of store, including but notlimited to a database (e.g., a relational database, anentity-relationship database, an object database, an object relationaldatabase, an XML database, etc.). Intent-based scheduling logic 302includes analysis logic 308, causation logic 310, inference logic 312,topic logic 314, identification logic 316, and determination logic 318.Further structural and operational embodiments will be apparent topersons skilled in the relevant art(s) based on the discussion regardingflowchart 200.

As shown in FIG. 2, the method of flowchart 200 begins at step 202. Instep 202, communication(s) from a first user are analyzed (e.g.,programmatically analyzed or processed) to identify a firstcommunication from the first user that indicates that the first user hasan intent to have a first meeting between at least the first user andsecond user(s). Examples of a communication include but are not limitedto a telephone call, an in-person conversation, a conversation via asoftware application (e.g., Skype®, developed and distributed originallyby Skype Technologies S.A.R.L. and subsequently by MicrosoftCorporation; Whatsapp® Messenger, developed and distributed by WhatsAppInc.; and Facebook® Messenger, developed and distributed by Facebook,Inc.), a voice mail, an email, a text message, a short message service(SMS) message, and a social update. In an example implementation,analysis logic 308 analyzes the communication(s) from the first user toidentify the first communication that indicates that the first user hasthe intent to have the first meeting. For instance, communication(s) 320may include the communication(s) from the first user. Thecommunication(s) 320 may be received (e.g., detected or sensed) via anysuitable interface, including but not limited to a sensor (e.g., amicrophone) or a digital interface (e.g., a digital receiver). Analysislogic 308 may include one or more such interfaces.

Analysis logic 308 may use any of a variety of techniques to determinethat the first communication indicates that the first user has theintent to have the first meeting. For example, analysis logic 308 mayuse natural language processing to infer the intent from the firstcommunication. In accordance with this example, analysis logic 308 mayuse statistical analysis with regard to the communication(s) from thefirst user to determine likelihoods (e.g., statistical probabilities)that the first user has respective intents. Analysis logic 308 maycompare each of the likelihoods to a likelihood threshold. A likelihoodthat is greater than or equal to the likelihood threshold may indicatethat the first user has the intent with which the likelihoodcorresponds. A likelihood that is less than the likelihood threshold mayindicate that the first user does not have the intent with which thelikelihood corresponds. Accordingly, analysis logic 308 may determinethat the first communication indicates that the first user has theintent to have the first meeting based at least in part on naturallanguage processing of the first communication revealing that thelikelihood that the first user has the intent to have the first meetingis greater than or equal to the likelihood threshold.

In another example, analysis logic 308 may analyze keywords in the firstcommunication to determine that the first communication indicates thatthe first user has the intent to have the first meeting. In accordancewith this example, analysis logic 308 may identify keywords in thecommunication(s) from the first user. Analysis logic 308 may comparekeywords that are identified in the first communication to referencekeywords to determine whether one or more of the keywords that areidentified in the first communication are the same or semantically thesame as one or more of the reference keywords. Each of the referencekeywords may be associated with one or more intents. Accordingly, akeyword that is identified in the first communication being the same orsemantically the same as a reference keyword may indicate that the firstuser has the intent(s) with which the reference keyword is associated.

In accordance with this example, one or more probabilities may beassociated with each reference keyword. Each probability may indicate alikelihood that a user whose communication includes a keyword thatmatches the reference keyword has an intent with which the referencekeyword is associated. Some reference keywords may be associated withone or more common (i.e., same) intent(s). Analysis logic 308 maydetermine a cumulative probability that a user has an intent bycombining (e.g., adding) the probabilities regarding the intent that areassociated with the various reference keywords based at least in part onkeywords in the user's communication(s) matching the reference keywords.If the cumulative probability is greater than or equal to a probabilitythreshold, the user may be deemed to have the intent. If the cumulativeprobability is less than the probability threshold, the user may bedeemed to not have the intent.

Accordingly, analysis logic 308 may determine that the firstcommunication from the first user indicates that the first user has theintent to have the first meeting based at least in part on a combinationof probabilities regarding the intent, which are associated withreference keywords that match keywords in the first communication, beinggreater than or equal to a probability threshold. Analysis logic 308 maygenerate an intent indicator 326 to specify that the first user has theintent to have the first meeting.

At step 204, communication(s) from the second user(s) are analyzed toidentify second communication(s) from the second user(s) that are inresponse to the first communication and that indicate that the seconduser(s) have the intent to have the first meeting. In an exampleimplementation, analysis logic 308 analyzes the communication(s) fromthe second user(s) to identify the second communication(s) that indicatethat the second user(s) have the intent to have the first meeting. Forinstance, the communication(s) 320 may include the communication(s) fromthe second user(s). In accordance with this implementation, the secondcommunication(s) may confirm that the second user(s) share the firstuser's intent to have the first meeting. The intent indicator 326 mayspecify that the second user(s) have the intent to have the firstmeeting. For example, the intent indicator 326 may indicate that thefirst user and the second user(s) share the intent to have the firstmeeting. Analysis logic 308 may use any of a variety of techniques todetermine that the second communication indicates that the seconduser(s) have the intent to have the first meeting, including but notlimited to natural language processing and keyword analysis.

At step 206, the digital personal assistant is caused to automaticallypropose and/or automatically schedule a time to have the first meetingbetween at least the first user and the second user(s) based at least inpart on the first communication and the second communication(s)indicating that the first user and the second user(s) have the intent tohave the first meeting. In an example implementation, causation logic310 causes digital personal assistant 306 to automatically proposeand/or automatically schedule a time to have the first meeting betweenat least the first user and the second user(s) based at least in part onthe first communication and the second communication(s) indicating thatthe first user and the second user(s) have the intent to have the firstmeeting. For example, causation logic 310 may cause digital personalassistant 306 to automatically propose and/or automatically schedule thetime to have the first meeting in response to receipt of the intentindicator 326. In accordance with this example, causation logic 310 maycause digital personal assistant 306 to automatically propose and/orautomatically schedule the time based at least in part on the intentindicator 326 specifying that the first user and the second user(s) havethe intent to have the first meeting. For instance, causation logic 310may cause digital personal assistant 306 to automatically propose and/orautomatically schedule the time based at least in part on the intentindicator 326 indicating that the second user(s) share the first user'sintent to have the first meeting.

Causation logic 310 may cause digital personal assistant 306 toautomatically propose and/or automatically schedule the time to have thefirst meeting between at least the first user and the second user(s) inany of a variety of ways. For instance, causation logic 310 may generatea scheduling instruction 342 in response to the receipt of the intentindicator 326. The scheduling instruction 342 instructs digital personalassistant 306 to perform scheduling operation(s) 344. The schedulingoperation(s) 344 include automatically proposing and/or automaticallyscheduling the time to have the first meeting between at least the firstuser and the second user(s).

In an example embodiment, causing the digital personal assistant toautomatically propose and/or automatically schedule the time to have thefirst meeting at step 206 includes causing the digital personalassistant to automatically schedule the time to have the first meeting.In accordance with this embodiment, the digital personal assistant iscaused to automatically configure a visual representation of calendar(s)of the respective second user(s) to indicate that attendance of thesecond user(s) at the meeting is tentative. In an aspect of thisembodiment, another digital personal assistant may be caused toautomatically configure a visual representation of a calendar of thefirst user to indicate that attendance of the first user at the meetingis tentative.

In some example embodiments, one or more steps 202, 204, and/or 206 offlowchart 200 may not be performed. Moreover, steps in addition to or inlieu of steps 202, 204, and/or 206 may be performed. For instance, in anexample embodiment, the method of flowchart 200 further includesdetermining a topic of the first meeting. For example, topic logic 314may determine the topic of the first meeting. In accordance with thisexample, store 304 may store meeting information 334. The meetinginformation 334 may include topic information regarding the topic of thefirst meeting. Topic logic 314 may receive (e.g., collect, retrieve) atleast the topic information. Topic logic 314 may determine the topic ofthe first meeting based at least in part on the topic informationspecifying the topic of the first meeting. Topic logic 314 may generatea topic indicator 330 in response to determining the topic of the firstmeeting. The topic indicator 330 may specify the topic of the firstmeeting.

In accordance with this embodiment, the method of flowchart 200 furtherincludes identifying a third user who has an attribute that correspondsto the topic. For example, identification logic 316 may identify thethird user. In accordance with this example, store 304 may store userinformation 332. The user information 332 may include cross-referenceinformation that cross-references attributes of users and topics.Accordingly, each user may have one or more attributes, each of whichmay correspond to one or more of the topics. Identification logic 316may review the cross-reference information to determine thatattribute(s) of the third user correspond to the topic of the firstmeeting. For instance, identification logic 316 may review thecross-reference information to find the topic of the first meeting amongthe topics that are listed in the cross-reference information.Identification logic 316 may then determine which attributes of theusers are indicated by the cross-reference information to becross-referenced with the topic. The attribute of the third user may beamong the attributes of the users that are indicated by thecross-reference information to be cross-referenced with the topic.Identification logic 316 may identify the third user based at least inpart on the attribute of the third user being cross-referenced with thetopic of the first meeting by the cross-reference information.Identification logic 316 may generate a user indicator 338 in responseto identifying the third user. The user indicator 338 may specify thatthe third user has an attribute that corresponds to the topic of thefirst meeting.

In further accordance with this embodiment, the method of flowchart 200further includes causing the digital personal assistant to suggest thatthe third person be invited to the first meeting based at least in parton the third user having the attribute that corresponds to the topic.For example, causation logic 310 may cause digital personal assistant306 to suggest that the third user be invited to the first meeting. Inaccordance with this example, causation logic 310 may cause the digitalpersonal assistant 306 to suggest that the third user be invited to thefirst meeting based at least in part on the user indicator 338specifying that the third user has an attribute that corresponds to thetopic of the first meeting.

In another example embodiment, the method of flowchart 200 furtherincludes inferring that a document is relevant to the first meeting. Forexample, inference logic 312 may infer that the document is relevant tothe first meeting. Accordingly, inference logic 312 may determine thatthe document is relevant to the first meeting based on an inference 324,which indicates that the document is relevant to the first meeting.Inference logic 312 may generate a relevance indicator 322 in responseto inferring that the document is relevant to the first meeting and/oran importance indicator 328. The relevance indicator 322 may specifythat the document is relevant to the first meeting.

In accordance with this embodiment, the method of flowchart 200 furtherincludes causing the digital personal assistant to attach (e.g.,automatically attach) the document to a calendar entry that representsthe first meeting based at least in part on an inference that thedocument is relevant to the first meeting. For example, causation logic310 may cause digital personal assistant 306 to attach the document tothe calendar entry based at least in part on the inference 324.

In an aspect of this embodiment, inferring that the document is relevantto the first meeting includes determining a topic of the first meeting.For instance, topic logic 314 may determine the topic of the firstmeeting. In accordance with this aspect, inferring that the document isrelevant to the first meeting further includes determining attributes ofmultiple documents. For example, inference logic 312 may determine theattributes of the documents. In further accordance with this aspect,inferring that the document is relevant to the first meeting furtherincludes determining that an attribute of the document corresponds tothe topic. For instance, inference logic 312 may determine that theattribute of the document corresponds to the topic. In furtheraccordance with this aspect, causing the digital personal assistant toattach the document to the calendar entry includes causing the digitalpersonal assistant to attach the document to the calendar entry based atleast in part on the attribute of the document corresponding to thetopic.

In yet another example embodiment, the method of flowchart 200 furtherincludes inferring a title of the first meeting from (a) at least one ofthe communication(s) from the first user and/or (b) at least one of thecommunication(s) from the second user(s). For example, inference logic312 may infer the title of the first meeting from the communication(s)320, including at least one of the communication(s) from the first userand/or at least one of the communication(s) from the second user(s). Inaccordance with this example, the inference 324 may indicate the title.In an aspect of this example, causing the digital personal assistant toautomatically propose and/or automatically schedule the time to have thefirst meeting at step 206 may include generating (e.g., automaticallygenerating) an invitation to the first meeting that specifies the titleof the first meeting, which is inferred from (a) at least one of thecommunication(s) from the first user and/or (b) at least one of thecommunication(s) from the second user(s).

In still another example embodiment, the method of flowchart 200 furtherincludes inferring an agenda of the first meeting from (a) at least oneof the communication(s) from the first user and/or (b) at least one ofthe communication(s) from the second user(s). For example, inferencelogic 312 may infer the agenda of the first meeting from thecommunication(s) 320, including at least one of the communication(s)from the first user and/or at least one of the communication(s) from thesecond user(s). In accordance with this example, the inference 324 mayindicate the agenda. In an aspect of this example, causing the digitalpersonal assistant to automatically propose and/or automaticallyschedule the time to have the first meeting at step 206 may includegenerating (e.g., automatically generating) an invitation to the firstmeeting that specifies the agenda of the first meeting, which isinferred from (a) at least one of the communication(s) from the firstuser and/or (b) at least one of the communication(s) from the seconduser(s).

In another example embodiment, the method of flowchart 200 furtherincludes automatically generating notes from communications among atleast the first user and the second user(s) that occur during themeeting. For instance, analysis logic 308 may generate notes 336 fromthe communication(s) 320, which may include the communications among atleast the first user and the second user(s) that occur during themeeting. In accordance with this embodiment, the method of flowchart 200further includes causing the digital personal assistant to provide thenotes to (a) the first user and/or (b) at least one of the seconduser(s) in response to automatically generating the notes. For example,causation logic 310 may cause digital personal assistant 306 to providethe notes 336 to the first user and/or at least one of the seconduser(s) in response to receipt of the notes 336 from analysis logic 308.

In yet another example embodiment, the method of flowchart 200 furtherincludes determining that an amount of information that is to bediscussed during the first meeting is not capable of being discussedwithin an amount of time that is allocated for the first meeting. Forexample, determination logic 318 may determine that the amount ofinformation that is to be discussed during the first meeting is notcapable of being discussed within the amount of time that is allocatedfor the first meeting. In accordance with this example, determinationlogic 318 may generate a follow-up instruction 340 in response todetermining that the amount of information that is to be discussedduring the first meeting is not capable of being discussed within theamount of time that is allocated for the first meeting. The follow-upinstruction 340 may specify that a follow-up meeting is to be scheduled.For instance, the follow-up instruction 340 may instruct causation logic310 to cause digital personal assistant 306 to schedule the follow-upmeeting for discussion of the information that is not discussed duringthe first meeting.

In accordance with this embodiment, the method of flowchart 200 furtherincludes causing the digital personal assistant to automaticallyschedule a follow-up meeting for discussion of the information that isnot discussed during the first meeting. For example, causation logic 310may cause digital personal assistant 306 to automatically schedule thefollow-up meeting. In accordance with this example, causation logic 310may cause digital personal assistant 306 to automatically schedule thefollow-up meeting in response to receipt of the follow-up instruction340. For instance, causation logic 310 may cause digital personalassistant 306 to automatically schedule the follow-up meeting based atleast in part on the follow-up instruction 340 specifying that thefollow-up meeting is to be scheduled.

In still another example embodiment, the method of flowchart 200 furtherincludes automatically monitoring conversations between the first userand other user(s) across multiple types of communication channels.Examples of a type of communication channel include but are not limitedto a wired or wireless telephone connection, an in-person communicationchannel, a software application (e.g., Skype®, Whatsapp® Messenger, orFacebook® Messenger), an email communication channel, a text messagingcommunication channel, an SMS communication channel, and a social updatecommunication channel. In an example, analysis logic 308 mayautomatically monitor the conversations between the first user and theother user(s) across the types of communication channels. In an aspectof this example, analysis logic 308 ambiently monitors theconversations, such that analysis logic 308 serves as a third-partyobserver that does not participate in the conversations. In accordancewith this aspect, analysis logic 308 may operate in an “always on”(a.k.a. “always listening”) state in which analysis logic 308continuously monitors for audio and/or visual inputs. By operating inthe “always on” state, analysis logic 308 may detect communications thatare directed to or from the first user across any one or more of thetypes of communication channels in absence of an instruction from thefirst user to do so.

In accordance with this embodiment, the communication(s) from the firstuser, which are analyzed at step 202, include communications that arefrom the conversations and that are received via the types ofcommunication channels. For example, the communication(s) 320 mayinclude communications from the conversations between the first user andthe other user(s) and that are received via the types of communicationchannels. In accordance with this example, a first subset of thecommunications may be received via a first type of communicationchannel. A second subset of the communications may be received via asecond type of communication channel, which is different from the firsttype, and so on.

In another example embodiment, the method of flowchart 200 furtherincludes inferring an importance of the first meeting. For example, theimportance of the first meeting may be inferred from communication(s)regarding the first meeting, a frequency of interaction between thefirst user and at least one of the second user(s), a number ofinteractions between the first user and at least one of the seconduser(s), an amount of time that the first user and at least one of thesecond user(s) spend together (e.g., working on projects, in a socialsetting, at work, or in total), a relationship between the first userand at least one of the second user(s), a number of projects that thefirst user has with at least one of the second user(s), an associationof the first user and/or at least one of the second user(s) with aproject to which the first meeting pertains, an amount of time the firstuser and/or at least one of the second users devotes to subject matterthat is to be discussed at the first meeting, and/or an extent ofknowledge that the first user and/or at least one of the second user(s)has regarding subject matter of the first meeting. A relationship of thefirst user with any one or more of the second user(s) may be determineby reviewing a family diagram or an organizational diagram that isassociated with the first user. The family diagram may specify familialrelationships between members in a family of the first user. Theorganization diagram may specify a hierarchy of employees in a companywith which the first user is employed. The family diagram and/or theorganizational diagram may be inferred by inference logic 312 orretrieved from store 304 by identification logic 316, though the scopeof the example embodiments is not limited in this respect. In an exampleimplementation, inference logic 312 infers the importance of the firstmeeting.

In a first aspect of this embodiment, causing the digital personalassistant to automatically propose and/or automatically schedule thetime to have the first meeting includes causing the digital personalassistant to automatically reduce a duration of a second meeting toaccommodate the first meeting based at least in part on an inferencethat the importance of the first meeting is greater than an importanceof the second meeting. For example, the importance of the second meetingmay be inferred based at least in part on who proposed the secondmeeting. In accordance with this example, causing the digital personalassistant to automatically reduce the duration of the second meeting maybe performed in response to inferring the importance of the secondmeeting. In another example, causing the digital personal assistant toautomatically reduce the duration of the second meeting may includeautomatically changing a representation of the second meeting on avisual representation of a calendar of the first user and/or at leastone of the second user(s) to indicate that the duration of the secondmeeting is reduced.

In another aspect of this embodiment, causing the digital personalassistant to automatically propose and/or automatically schedule thetime to have the first meeting includes causing the digital personalassistant to automatically cancel a second meeting to accommodate thefirst meeting based at least in part on an inference that the importanceof the first meeting is greater than an importance of the secondmeeting. For instance, causing the digital personal assistant toautomatically cancel the second meeting may include automaticallydeleting a representation of the second meeting from a visualrepresentation of a calendar of the first user and/or at least one ofthe second user(s) to indicate that the second meeting is cancelled.

In yet another aspect of this embodiment, causing the digital personalassistant to automatically propose and/or automatically schedule thetime to have the first meeting includes causing the digital personalassistant to automatically reschedule and/or automatically propose toreschedule a second meeting to accommodate the first meeting based atleast in part on an inference that the importance of the first meetingis greater than an importance of the second meeting. For example,causing the digital personal assistant to automatically rescheduleand/or automatically propose to reschedule the second meeting includescausing the digital personal assistant to automatically rescheduleand/or automatically propose to reschedule the second meeting at whichthe first user is scheduled to attend to accommodate the first meetingbased at least in part on an inference that the importance of the firstmeeting to the first user is greater than the importance of the secondmeeting to the first user. In another example, causing the digitalpersonal assistant to automatically reschedule and/or automaticallypropose to reschedule the second meeting includes causing the digitalpersonal assistant to automatically reschedule and/or automaticallypropose to reschedule the second meeting at which at least one of thesecond user(s) is scheduled to attend to accommodate the first meetingbased at least in part on an inference that the importance of the firstmeeting to the at least one second user is greater than the importanceof the second meeting to the at least one second user.

In an example of this aspect, causing the digital personal assistant toautomatically reschedule and/or automatically propose to reschedule thesecond meeting includes causing the digital personal assistant toautomatically reschedule the second meeting to accommodate the firstmeeting. In accordance with this example, causing the digital personalassistant to automatically reschedule the second meeting to accommodatethe first meeting may include one or more of the steps shown inflowchart 400 of FIG. 4. Flowchart 400 may be performed by causationlogic 310 shown in FIG. 3, for example. For illustrative purposes,flowchart 400 is described with respect to causation logic 500 of FIG.5, which is an example of causation logic 310, according to anembodiment. As shown in FIG. 5, causation logic 500 includes a calendaranalyzer 502, an inquiry provider 504, and a time changer 506. Furtherstructural and operational embodiments will be apparent to personsskilled in the relevant art(s) based on the discussion regardingflowchart 400.

Before discussing flowchart 400, it should be mentioned that computingsystem 300 may not include one or more of intent-based scheduling logic302, store 304, digital personal assistant 306, analysis logic 308,causation logic 310, inference logic 312, topic logic 314,identification logic 316, and/or determination logic 318. Furthermore,computing system 300 may include components in addition to or in lieu ofintent-based scheduling logic 302, store 304, digital personal assistant306, analysis logic 308, causation logic 310, inference logic 312, topiclogic 314, identification logic 316, and/or determination logic 318.

As shown in FIG. 4, the method of flowchart 400 begins at step 402. Instep 402, at least one calendar of at least one respective second userof the second user(s) is automatically analyzed to determine time(s) atwhich the at least one second user is available to have the secondmeeting. In an example implementation, calendar analyzer 502automatically analyzes calendar(s) 508 of at least one second user todetermine the time(s) at which the at least one second user is availableto have the second meeting. Calendar analyzer 502 may generate a timeindicator 512 in response to determining the time(s) at which the atleast one second user is available to have the second meeting. The timeindicator 512 may specify the time(s) at which the at least one seconduser is available to have the second meeting.

At step 404, an inquiry is automatically provided to specified user(s)who are scheduled to attend the second meeting. The inquiry presents atleast one time as a possible time at which to conduct the secondmeeting. In an example implementation, inquiry provider 504automatically provides an inquiry 514 to the specified user(s) who arescheduled to attend the second meeting. The inquiry presents at leastone time as a possible time at which to conduct the second meeting.

At step 406, a response to the inquiry is received that indicatesselection of a designated time from the at least one time by at leastone of the user(s) who are scheduled to attend the second meeting. In anexample implementation, time changer 506 receives a response 510 to theinquiry 514 that indicates selection of the designated time from the atleast one time.

At step 408, the time at which the second meeting is to be conducted ischanged to the designated time based at least in part on the response tothe inquiry indicating selection of the designated time. In an exampleimplementation, time changer 506 changes the time at which the secondmeeting is to be conducted to the designated time based at least in parton the response 510 to the inquiry 514 indicating the selection of thedesignated time. For instance, time changer 506 may access calendar(s)(e.g., electronic calendar(s) in calendar application(s)) of at leastone second user and/or at least one of the specified user(s) to updatethe time at which the second meeting is to be conducted to thedesignated time in the calendar(s).

It will be recognized that causation logic 500 may not include one ormore of calendar analyzer 502, inquiry provider 504, and/or time changer506. Furthermore, causation logic 500 may include components in additionto or in lieu of calendar analyzer 502, inquiry provider 504, and/ortime changer 506.

FIGS. 6-7 depict flowcharts 600 and 700 of other example methods forperforming intent-based scheduling via a digital personal assistant inaccordance with embodiments. Flowcharts 600 and 700 may be performed byintent-based scheduling logic 110 shown in FIG. 1, for example. Forillustrative purposes, flowcharts 600 and 700 are described with respectto computing system 800 shown in FIG. 8. Computing system 800 mayinclude one or more of user systems 102A-102M, one or more of server(s)106A-106N, or any combination thereof, though the scope of the exampleembodiments is not limited in this respect. Computing system 800includes intent-based scheduling logic 802, which is an example ofintent-based scheduling logic 110, according to an embodiment. As shownin FIG. 8, computing system 800 further includes a store 804 and adigital personal assistant 806. Intent-based scheduling logic 802includes identification logic 808, causation logic 810, inference logic812, topic logic 814, selection logic 816, determination logic 818, andattribute logic 820. Further structural and operational embodiments willbe apparent to persons skilled in the relevant art(s) based on thediscussion regarding flowcharts 600 and 700.

As shown in FIG. 6, the method of flowchart 600 begins at step 602. Instep 602, interactions among users are identified. Examples of aninteraction include but are not limited to a meeting and a conversation.In an example implementation, identification logic 808 identifies theinteractions among the users. For example, identification logic 808 mayreceive interaction information 822. Interaction information 822 mayinclude a representation of content of the interactions, indications oftools that are used to facilitate the interactions, informationregarding which of the users initiates each interaction, and informationregarding which of the users participate in each interaction. Theinteraction information 822 may include an audio representation of oneor more of the interactions, a video representation of one or more ofthe interactions, and/or a textual representation of one or more of thetransactions. The interaction information 822 may include atranscription of one or more of the interactions, keywords extractedfrom one or more of the interactions, etc.

At step 604, tools that are used to facilitate the interactions areidentified. In an example implementation, identification logic 808identifies the tools that are used to facilitate the interactions. Forexample, identification logic 808 may identify the tools in response toreceipt of the interaction information 822. In accordance with thisexample, the interaction information 822 may indicate (e.g., specify)the tools that are used to facilitate the interactions. Identificationlogic 808 may generate tool information 832 in response to receipt ofthe interaction information 822. The tool information 832 may specifythe tools that are used to facilitate the interactions. For instance,tool information 832 may specify one or more tools that are used tofacilitate each of the interactions. Examples of a tool include but arenot limited to a telephone, a software application (e.g., Skype®,Whatsapp® Messenger, or Facebook® Messenger), email, text message, SMSmessage, teleconference bridge, in-person (a.k.a. face-to-face)engagement, and a location (e.g., room) in which an interaction occurs.

At step 606, an intent to have a meeting between the users is inferred(e.g., programmatically inferred). For example, the intent to have themeeting may be inferred from communications among at least some of theusers, historical interactions among at least some of the users, acorporate announcement that affects project(s) to which the userscontribute, a milestone, etc. Examples of a milestone include but arenot limited to an anniversary, a birthday, and achieving a corporategoal (e.g., reaching a threshold number of sales or a thresholdrevenue). In an example implementation, inference logic 812 infers theintent to have the meeting. For instance, inference logic 812 may inferthe intent from the interaction information 822. Inference logic 812 maygenerate intent indicator 826 in response to inferring the intent. Theintent indicator 826 specifies the intent to have the meeting betweenthe users.

At step 608, a designated tool is automatically selected to establishcommunication for the meeting based at least in part on the designatedtool being used more (e.g., more often or more frequently) than othertools to facilitate the interactions. In an example implementation,selection logic 816 selects the designated tool to establishcommunication for the meeting. Selection logic 816 may select thedesignated tool in response to receipt of the tool information 832. Forinstance, selection logic 816 may analyze the tool information 832 todetermine that the designated tool is used more than the other tools tofacilitate the interactions. Selection logic 816 may generate aselection indicator 846 in response to automatically selecting thedesignated tool. The selection indicator 846 may specify that thedesignated tool is selected to establish communication for the meeting.The selection indicator 846 may instruct causation logic 810 to causedigital personal assistant 806 to use the designated tool to establishcommunication for the meeting.

At step 610, the digital personal assistant is caused to automaticallyschedule the meeting and/or automatically propose to schedule themeeting based at least in part on an inference of the intent to have themeeting. In an example implementation, causation logic 810 causesdigital personal assistant 806 to automatically schedule the meetingand/or automatically propose to schedule the meeting. For example,causation logic 810 may cause digital personal assistant 806 toautomatically schedule the meeting and/or automatically propose toschedule the meeting to use the designated tool to establishcommunication for the meeting. In accordance with this example,causation logic 810 may configure a connection that utilizes thedesignated tool for use during the meeting in order to enablecommunication via the connection to occur during the meeting. Causationlogic 810 may cause digital personal assistant 806 to automaticallyschedule the meeting and/or automatically propose to schedule themeeting in response to receipt of the intent indicator 826. Forinstance, causation logic 810 may cause digital personal assistant 806to automatically schedule the meeting and/or automatically propose toschedule the meeting based at least in part on the intent indicator 826specifying the intent to have the meeting between the users.

Causation logic 810 may cause digital personal assistant 806 toautomatically schedule the meeting and/or automatically propose toschedule the meeting in any of a variety of ways. For instance,causation logic 810 may generate a scheduling instruction 842 inresponse to the receipt of the intent indicator 826. The schedulinginstruction 842 instructs digital personal assistant 806 to performscheduling operation(s) 844. The scheduling operation(s) 844 includeautomatically scheduling the meeting and/or automatically proposing toschedule the meeting.

In some example embodiments, one or more steps 602, 604, 606, 608,and/or 610 of flowchart 600 may not be performed. Moreover, steps inaddition to or in lieu of steps 602, 604, 606, 608, and/or 610 may beperformed. For instance, in an example embodiment, the method offlowchart 600 further includes determining a topic of the meeting. Forexample, topic logic 814 may determine the topic of the meeting. Inaccordance with this example, topic logic 814 may determine the topic ofthe meeting based at least in part on the interaction information 822indicating (e.g., specifying) the topic of the meeting. For instance,topic logic 814 may infer the topic of the meeting from the interactioninformation 822. Topic logic 814 may generate a topic indicator 830 inresponse to determining the topic of the meeting. The topic indicator830 may specify the topic of the meeting.

In a first aspect of this embodiment, the method of flowchart 600further includes determining that attribute(s) of a designated usercorrespond to the topic. In an example implementation, attribute logic820 determines that the attribute(s) of the designated user correspondto the topic. In accordance with this implementation, store 804 storesuser information 834. Attribute logic 820 may receive (e.g., collect,retrieve) the user information 834 from store 804. The user information834 may specify attributes of the users. For instance, the userinformation 834 may specify one or more attributes for each of theusers. The user information 834 may include cross-reference informationthat cross-references the attributes of the users and topics.Accordingly, each attribute of a user may correspond to one or more ofthe topics. Attribute logic 820 may review the cross-referenceinformation to determine that the attribute(s) of the designated usercorrespond to the topic of the meeting.

For instance, attribute logic 820 may review the topic indicator 830 todetermine the topic of the meeting. Attribute logic 820 may review thecross-reference information to find the topic of the meeting among thetopics that are listed in the cross-reference information. Attributelogic 820 may then determine which attributes of the users are indicatedby the cross-reference information to be cross-referenced with the topicof the meeting. The attribute(s) of the designated user may be among theattributes of the users that are indicated by the cross-referenceinformation to be cross-referenced with the topic of the meeting.Attribute logic 820 may determine that the attribute(s) of thedesignated user correspond to the topic of the meeting based at least inpart on the attribute(s) of the designated user being cross-referencedwith the topic of the meeting by the cross-reference information.Attribute logic 820 may generate correspondence information 840 inresponse to determining that the attribute(s) of the designated usercorrespond to the topic of the meeting. The correspondence information840 may specify that the attribute(s) of the designated user correspondto the topic of the meeting.

In accordance with this aspect, causing the digital personal assistantto automatically schedule the meeting and/or automatically propose toschedule the meeting at step 610 includes causing the digital personalassistant to automatically schedule the meeting, including causing thedigital personal assistant to automatically specify that attendance ofthe designated user at the meeting is required based at least in part onthe attribute(s) of the designated user corresponding to the topic. Forexample, causation logic 810 may cause digital personal assistant 806 toautomatically specify that attendance of the designated user at themeeting is required in response to receipt of the correspondenceinformation 840. In accordance with this example, causation logic 810may cause digital personal assistant 806 to automatically specify thatattendance of the designated user at the meeting is required based atleast in part on the correspondence information 840 specifying that theattribute(s) of the designated user correspond to the topic of themeeting.

In a second aspect of this embodiment, the method of flowchart 600further includes determining that a designated user does not have atleast one attribute that corresponds to the topic. In an exampleimplementation, attribute logic 820 determines that the designated userdoes not have at least one attribute that corresponds to the topic. Inaccordance with this implementation, attribute logic 820 may reviewcross-reference information, which is included in the user information834, to determine that the designated user does not have at least oneattribute that corresponds to the topic.

For instance, attribute logic 820 may review the topic indicator todetermine the topic of the meeting. Attribute logic 820 may review thecross-reference information to find the topic of the meeting among thetopics that are listed in the cross-reference information. Attributelogic 820 may then determine which attributes of the users are indicatedby the cross-reference information to be cross-referenced with the topicof the meeting. No attributes of the designated user may be among theattributes of the users that are indicated by the cross-referenceinformation to be cross-referenced with the topic of the meeting.Attribute logic 820 may determine that the designated user does not haveat least one attribute that corresponds to the topic based at least inpart on the designated user not having any attributes that are indicatedby the cross-reference information to be cross-referenced with the topicof the meeting. Attribute logic 820 may generate correspondenceinformation 840 in response to determining that the designated user doesnot have at least one attribute that corresponds to the topic. Thecorrespondence information 840 may specify that the designated user doesnot have at least one attribute that corresponds to the topic.

In an example of this aspect, causing the digital personal assistant toautomatically schedule the meeting and/or automatically propose toschedule the meeting at step 610 includes causing the digital personalassistant to automatically schedule the meeting, including causing thedigital personal assistant to automatically specify that attendance ofthe designated user at the meeting is optional based at least in part onthe designated user not having at least one attribute that correspondsto the topic.

In another example of this aspect, causing the digital personalassistant to automatically schedule the meeting and/or automaticallypropose to schedule the meeting at step 610 includes causing the digitalpersonal assistant to automatically schedule the meeting, includingcausing the digital personal assistant to not invite the designated userto attend the meeting based at least in part on the designated user nothaving at least one attribute that corresponds to the topic. Forinstance, causing the digital personal assistant to not invite thedesignated user to attend the meeting may include causing the digitalpersonal assistant to not include the designated user in a list ofinvitees to whom an invitation to the meeting is provided.

In another example embodiment, the method of flowchart 600 furtherincludes inferring an importance of the meeting to each of the users.For example, the importance of the meeting to each of the users may beinferred from communication(s) to or from the user regarding themeeting, a frequency of interaction between the user and the otherusers, a number of interactions between the user and at least one of theother users, an amount of time that the user and at least one of theother users spend together (e.g., working on projects, in a socialsetting, at work, or in total), a relationship between the user and atleast one of the other users, a number of projects that the user haswith at least one of the other users, an association of the user with aproject to which the meeting pertains, an extent of knowledge that theuser has regarding subject matter of the meeting, an amount of time theuser spends on subject matter to which the meeting pertains, and/or whoproposed the meeting (e.g., whether the user, a manager of the user, afamily member of the user, or a friend of the user proposed themeeting). In an example implementation, inference logic 312 infers theimportance of the meeting. For instance, inference logic 312 may inferthe importance of the meeting based at least in part on the interactioninformation 822, which may include information regarding any one or moreof the example factors mentioned above.

In accordance with this embodiment, causing the digital personalassistant to automatically schedule the meeting and/or automaticallypropose to schedule the meeting at step 610 includes causing the digitalpersonal assistant to invite a first subset of the users to attend themeeting based at least in part on the importance of the meeting to eachuser in the first subset reaching a threshold importance and to notinvite a second subset of the users to attend the meeting based at leastin part on the importance of the meeting to each user in the secondsubset not reaching the threshold importance. For instance, causing thedigital personal assistant to invite the first subset of the users toattend the meeting and to not invite the second subset of the users toattend the meeting may include causing the digital personal assistant toinclude each user in the first subset in a list of invitees to whom aninvitation to the meeting is provided and to not include each user inthe second subset in the list.

In yet another example embodiment, the method of flowchart 600 furtherincludes automatically monitoring conversations among the users acrossmultiple types of communication channels. For example, identificationlogic 808 may automatically monitor the conversations among the usersacross the types of communication channels. In accordance with thisexample, identification logic 808 may ambiently monitor theconversations. For instance, identification logic 808 may serve as athird-party observer that does not participate in the conversations.Identification logic 808 may operate in an “always on” (a.k.a. “alwayslistening”) state in which identification logic 808 continuouslymonitors for audio and/or visual inputs, though the scope of the exampleembodiments is not limited in this respect.

In accordance with this embodiment, identifying the interactions at step602 includes identifying the interactions that are included in theconversations and that are received via the types of communicationchannels. For example, a first subset of the interactions may bereceived via a first type of communication channel. A second subset ofthe interactions may be received via a second type of communicationchannel, which is different from the first type, and so on.

In still another example embodiment, the method of flowchart 600 furtherincludes one or more of the steps shown in flowchart 700 of FIG. 7. Inaccordance with this embodiment, causing the digital personal assistantto automatically schedule the meeting and/or automatically propose toschedule the meeting includes causing the digital personal assistant toautomatically schedule the meeting, including causing the digitalpersonal assistant to automatically invite at least a subset of theusers to attend the meeting.

As shown in FIG. 7, the method of flowchart 700 begins at step 702. Instep 702, a determination is made that user(s) in the subset decline aninvitation to the meeting. In an example implementation, determinationlogic 818 determines that the user(s) in the subset decline theinvitation. For instance, determination logic 818 may determine that theuser(s) in the subset decline the invitation in response to receipt ofinvitation information 838. The invitation information 838 may specifythat the user(s) in the subset decline the invitation. The invitationinformation 838 may further specify that one or more other users acceptthe invitation, though the scope of the example embodiments is notlimited in this respect. Determination logic 818 may determine that theuser(s) in the subset decline the invitation based at least in part onthe invitation specifying that the user(s) in the subset decline theinvitation. Determination logic 818 may generate subset information 824in response to determining that the user(s) in the subset decline theinvitation. The subset information 824 may indicate that the user(s) inthe subset decline the invitation.

At step 704, an importance of each user in the subset to attend themeeting is inferred. In an example implementation, inference logic 812infers how important it is for each user in the subset to attend themeeting. For instance, inference logic 812 may infer the importance ofeach user in the subset to attend the meeting based at least in part onthe interaction information 822 and/or the user information 834.Inference logic 812 may generate importance information 828 in responseto determining the importance of each user in the subset to attend themeeting. The importance information 812 may specify the importance ofeach user in the subset to attend the meeting.

At step 706, the digital personal assistant is caused to automaticallyreschedule the meeting to include each user in the subset who has animportance that is greater than or equal to a threshold importance andto not include each user in the subset who has an importance that isless than the threshold importance. For example, the digital personalassistant may be caused to automatically reschedule the meeting toinclude each user in the subset who has an importance that is greaterthan or equal to the threshold importance and to not include each userin the subset who has an importance that is less than the thresholdimportance in response to inferring the importance of each user in thesubset. At least one of the user(s) in the subset who decline theinvitation has an importance that is greater than or equal to thethreshold importance.

In an example implementation, causation logic 810 causes digitalpersonal assistant 806 to automatically reschedule the meeting toinclude each user in the subset who has an importance that is greaterthan or equal to the threshold importance and to not include each userin the subset who has an importance that is less than the thresholdimportance. For example, causation logic 810 may cause digital personalassistant 806 to automatically reschedule the meeting as described abovein response to receipt of the importance information 828 and/or thesubset information 824. In accordance with this example, causation logic810 may cause digital personal assistant 806 to automatically reschedulethe meeting as described above based at least in part on the subsetinformation 824 indicating that the user(s) in the subset decline theinvitation.

Causation logic 810 may compare the importance of each user in thesubset (e.g., as specified by the importance information 828) to thethreshold importance to determine which of the users in the subset havean importance that is greater than or equal to the threshold importanceand which of the users in the subset have an importance that is lessthan the threshold importance.

In an aspect of this embodiment, causing the digital personal assistantto automatically reschedule the meeting includes causing the digitalpersonal assistant to take into consideration a time zone of each userin the subset who has an importance that is greater than or equal to thethreshold importance to establish a time at which the meeting is tooccur. For instance, store 804 may store time zone information 836. Thetime zone information 836 may specify a time zone for any one or more ofthe users. For example, the time zone of each user may be a time zone inwhich the user works and/or lives. Causation logic 810 may receive(e.g., collect, retrieve) the time zone information 836 from store 804.Causation logic 810 may review the time zone information 836 todetermine the time zone of each user in the subset. Causation logic 810may then cause digital personal assistant 806 to take into considerationthe time zone of each user in the subset who has an importance that isgreater than or equal to the threshold importance to establish the timeat which the meeting is to occur.

It will be recognized that computing system 800 may not include one ormore of intent-based scheduling logic 802, store 804, digital personalassistant 806, identification logic 808, causation logic 810, inferencelogic 812, topic logic 814, selection logic 816, determination logic818, and/or attribute logic 820. Furthermore, computing system 800 mayinclude components in addition to or in lieu of intent-based schedulinglogic 802, store 804, digital personal assistant 806, identificationlogic 808, causation logic 810, inference logic 812, topic logic 814,selection logic 816, determination logic 818, and/or attribute logic820.

FIG. 9 depicts a flowchart 900 of yet another example method forperforming intent-based scheduling via a digital personal assistant inaccordance with an embodiment. Flowchart 900 may be performed byintent-based scheduling logic 110 shown in FIG. 1, for example. Forillustrative purposes, flowchart 900 is described with respect tocomputing system 1000 shown in FIG. 10. Computing system 1000 mayinclude one or more of user systems 102A-102M, one or more of server(s)106A-106N, or any combination thereof, though the scope of the exampleembodiments is not limited in this respect. Computing system 1000includes intent-based scheduling logic 1002, which is an example ofintent-based scheduling logic 110, according to an embodiment. As shownin FIG. 10, computing system 1000 further includes a digital personalassistant 1006. Intent-based scheduling logic 1002 includes analysislogic 1008 and causation logic 1010. Further structural and operationalembodiments will be apparent to persons skilled in the relevant art(s)based on the discussion regarding flowchart 900.

As shown in FIG. 9, the method of flowchart 900 begins at step 902. Instep 902, communication(s) from a first user are analyzed to infer(e.g., programmatically infer) from at least a first communication thatthe first user has an intent to perform an activity. Examples ofperforming an activity include but are not limited to having a meeting,working on a project, participating in a social event, exercising, andreading. In an example implementation, analysis logic 1008 analyzescommunication(s) 1020 from the first user. In accordance with thisimplementation, the communication(s) 1020 include at least the firstcommunication. Analysis logic 1008 infers from at least the firstcommunication that the first user has the intent to perform theactivity. Analysis logic 1008 may generate an intent indicator 1026 inresponse to inferring that the first user has the intent to perform theactivity. The intent indicator specifies that the first user has theintent to perform the activity.

At step 904, the digital personal assistant is caused to automaticallyschedule a designated time on a visual representation of a calendar ofthe first user to perform the activity, including causing the digitalpersonal assistant to automatically update the visual representation ofthe calendar to include a visual representation of the activity that isconfigured to indicate that the designated time is scheduled to performthe activity, based at least in part on an inference from at least thefirst communication that the first user has the intent to perform theactivity. In an example implementation, causation logic 1010 causesdigital personal assistant 1006 to automatically schedule the designatedtime on the visual representation of the calendar of the first user toperform the activity based at least in part on the inference from atleast the first communication that the first user has the intent toperform the activity. In accordance with this implementation, causationlogic 1010 causes digital personal assistant 1006 to automaticallyupdate the visual representation of the calendar to include the visualrepresentation of the activity based at least in part on the inferencefrom at least the first communication that the first user has the intentto perform the activity.

For example, causation logic 1010 may cause digital personal assistant1006 to access scheduling functionality of a calendar application thatmaintains the calendar of the first user. In accordance with thisexample, causation logic 1010 may cause digital personal assistant 1006to (a) add the activity on the calendar of the first user (e.g., as anappointment and/or a meeting) using the scheduling functionality and (b)specify that the activity is to occur at the designated time, which maycause the visual representation of the calendar to be automaticallyupdated in accordance with the scheduling functionality to include thevisual representation of the activity that is configured to indicatethat the designated time is scheduled to perform the activity.

Causation logic 1010 may cause digital personal assistant 1006 toautomatically schedule the designated time on the visual representationof the calendar of the first user in any of a variety of ways. Forinstance, causation logic 1010 may generate a scheduling instruction1042 in response to the receipt of the intent indicator 1026. Thescheduling instruction 1042 instructs digital personal assistant 1006 toperform scheduling operation(s) 1044. The scheduling operation(s) 1044include automatically scheduling the designated time on the visualrepresentation of the calendar of the first user.

In some example embodiments, one or more steps 902 and/or 904 offlowchart 900 may not be performed. Moreover, steps in addition to or inlieu of steps 902 and/or 904 may be performed. For instance, in anexample embodiment, the method of flowchart 900 further includesanalyzing communication(s) from a second user to identify an inquiryfrom the second user as to whether the first person is to perform theactivity. In an example implementation, analysis logic 1008 analyzes thecommunication(s) from the second user to identify the inquiry. Forinstance, the communication(s) 1020 may include the communication(s)from the second user. In accordance with this embodiment, the first userhaving the intent to perform the activity is inferred from at least thefirst communication in response to the inquiry being identified.

In another example embodiment, an importance of the activity is inferredfrom at least one of the communication(s). It will be recognized thatthe importance of the activity may be inferred from factor(s) inaddition to or in lieu of at least one of the communication(s). Forinstance, the importance of the activity may be inferred at least inpart from an amount of time the user spends on subject matter with whichthe activity relates. In one example, analysis logic 1008 may infer theimportance of the activity from communication(s) 1020. In accordancewith this example, analysis logic may generate an importance indicator1028 in response to inferring the importance of the activity. Theimportance indicator 1028 may specify the importance of the activity.

In a first aspect of this embodiment, causing the digital personalassistant to automatically schedule the designated time on the visualrepresentation of the calendar of the first user includes automaticallyrescheduling a second activity that is represented on the calendar toaccommodate the activity based at least in part on the importance of theactivity that is inferred from at least one of the communication(s)being greater than an importance of the second activity. For example, avisual representation of the second activity may be moved in the visualrepresentation of the calendar to a time that is different from thedesignated time. In accordance with this example, the visualrepresentation of the second activity may be moved so that the visualrepresentation of the second activity does not overlap a visualrepresentation of the activity, which is configured to indicate that thedesignated time is scheduled to perform the activity.

In a second aspect of this embodiment, causing the digital personalassistant to automatically schedule the designated time on the visualrepresentation of the calendar of the first user includes automaticallyreducing a duration of a second activity that is represented on thecalendar to accommodate the activity based at least in part on theimportance of the activity that is inferred from at least one of thecommunication(s) being greater than an importance of the secondactivity. For example, a size of a visual representation of the secondactivity may be reduced in the visual representation of the calendar toindicate that the duration of the second activity is reduced. Inaccordance with this example, the size of the visual representation ofthe second activity may be reduced by reducing a number of timeincrements that the visual representation of the second activity coversin the calendar to correspond to the reduced duration of the secondactivity.

In a third aspect of this embodiment, causing the digital personalassistant to automatically schedule the designated time on the visualrepresentation of the calendar of the first user includes automaticallycancelling a second activity to accommodate the activity based at leastin part on the importance of the activity that is inferred from at leastone of the communication(s) being greater than an importance of thesecond activity. For example, a visual representation of the secondactivity may be removed from the visual representation of the calendar(e.g., to indicate that the second activity is cancelled). In anotherexample, an opacity of the visual representation of the second activitymay be reduced to indicate that the second activity is cancelled. In yetanother example, the visual representation of the second activity ismarked in a way that indicates that the second activity is cancelled.

In yet another example embodiment, causing the digital personalassistant to automatically schedule the designated time includes causingthe digital personal assistant to automatically configure the visualrepresentation of the calendar of the first user, which is configuredfor viewing by at least one second user that is different from the firstuser, to indicate that availability of the first user at the designatedtime is tentative.

In an aspect of this embodiment, causing the digital personal assistantto automatically schedule the designated time further includes causingthe digital personal assistant to automatically configure a secondvisual representation of the calendar of the first user, which isconfigured for viewing by the first user, to indicate that theavailability of the first user at the designated time is free. Inaccordance with this aspect, the method of flowchart 900 may furtherinclude receiving an acceptance of an invitation to perform the activityat the designated time from the first user in response to causing thedigital personal assistant to automatically schedule the designated timeon the visual representation of the calendar to perform the activity.For instance, causation logic 1010 may receive an invitation acceptance1038 from the first user. The invitation acceptance 1038 may indicateacceptance of the invitation to perform the activity at the designatedtime.

In a first example of this aspect, the method of flowchart 900 furtherincludes causing the digital personal assistant to reconfigure thesecond visual representation of the calendar of the first user to changean indication of the availability of the first user at the designatedtime in the second visual representation from free to booked in responseto receiving the acceptance of the invitation. In a second example ofthis aspect, the method of flowchart 900 further includes causing thedigital personal assistant to reconfigure the visual representation ofthe calendar of the first user, which is for viewing by the at least onesecond user, to change an indication of the availability of the firstuser at the designated time in the visual representation from tentativeto booked in response to receiving the acceptance of the invitation.

In still another example embodiment, causing the digital personalassistant to automatically schedule the designated time includes causingthe digital personal assistant to automatically configure the visualrepresentation of the calendar of the first user, which is configuredfor viewing by the first user and not for viewing by second user(s), toindicate that availability of the first user at the designated time istentative or booked. In accordance with this embodiment, causing thedigital personal assistant to automatically schedule the designated timefurther includes causing the digital personal assistant to automaticallyconfigure a second visual representation of the calendar of the firstuser, which is configured for viewing by the second user(s), to indicatethat the availability of the first user at the designated time is free.

In an aspect of this embodiment, the method of flowchart 900 furtherincludes receiving an acceptance of an invitation to perform theactivity at the designated time from the first user in response tocausing the digital personal assistant to automatically schedule thedesignated time on the visual representation of the calendar to performthe activity. For instance, causation logic 1010 may receive theinvitation acceptance 1038 from the first user. The invitationacceptance 1038 may indicate acceptance of the invitation to perform theactivity at the designated time.

In a first example of this aspect, the method of flowchart 900 furtherincludes causing the digital personal assistant to reconfigure thesecond visual representation of the calendar of the first user to changean indication of the availability of the first user at the designatedtime in the second visual representation from free to booked in responseto receiving the acceptance of the invitation. In a second example ofthis aspect, the method of flowchart 900 further includes causing thedigital personal assistant to reconfigure the visual representation ofthe calendar of the first user, which is configured for viewing by thefirst user and not for viewing by the second user(s), to change anindication of the availability of the first user at the designated timein the visual representation from tentative to booked in response toreceiving the acceptance of the invitation.

In another example embodiment, the method of flowchart 900 furtherincludes automatically monitoring conversations between the first userand other user(s) across multiple types of communication channels. In anexample implementation, analysis logic 1008 monitors the conversationsbetween the first user and the other user(s) across the types ofcommunication channels. For instance, the communication(s) 1020 mayinclude the conversations.

It will be recognized that computing system 1000 may not include one ormore of intent-based scheduling logic 1002, digital personal assistant1006, analysis logic 1008, and/or causation logic 1010. Furthermore,computing system 1000 may include components in addition to or in lieuof intent-based scheduling logic 1002, digital personal assistant 1006,analysis logic 1008, and/or causation logic 1010.

FIG. 11 depicts a flowchart 1100 of still another example method forperforming intent-based scheduling via a digital personal assistant inaccordance with an embodiment. Flowchart 1100 may be performed byintent-based scheduling logic 110 shown in FIG. 1, for example. Forillustrative purposes, flowchart 1100 is described with respect tocomputing system 1200 shown in FIG. 12. Computing system 1200 mayinclude one or more of user systems 102A-102M, one or more of server(s)106A-106N, or any combination thereof, though the scope of the exampleembodiments is not limited in this respect. Computing system 1200includes intent-based scheduling logic 1202, which is an example ofintent-based scheduling logic 110, according to an embodiment. As shownin FIG. 12, computing system 1200 further includes a digital personalassistant 1206. Intent-based scheduling logic 1202 includes analysislogic 1208, causation logic 1210, inference logic 1212, anddetermination logic 1218. Further structural and operational embodimentswill be apparent to persons skilled in the relevant art(s) based on thediscussion regarding flowchart 1100.

As shown in FIG. 11, the method of flowchart 1100 begins at step 1102.In step 1102, instances of an action that are performed by a user atrespective historical time instances are analyzed to identify a trendwith regard to the instances of the action. In an exampleimplementation, analysis logic 1208 analyzes the instances of the actionto identify the trend. For example, action information 1204 may includeinformation regarding the instances of the action that are performed bythe user at the respective historical instances. In accordance with thisexample, the action information 1204 may serve as a log for a variety ofactions. Accordingly, action information 1204 may include an entry foreach instance of each action that is performed. The action information1204 may also specify which of a variety of users performed eachinstance of each action. Analysis logic 1208 may review the actioninformation 1204 to determine (e.g., identify) the instances of theaction that are performed by the user at the respective historical timeinstances. Analysis 1208 may analyze the instances of the action thatare performed by the user at the respective historical time instances toidentify the trend in response to determining the instances from theaction information 1204. Analysis logic 1208 may generate a trendindicator 1214 in response to identifying the trend. The trend indicator1214 may indicate the trend. For instance, the trend indicator mayspecify one or more attributes of the trend. Examples of an attribute ofthe trend include but are not limited to a shape (e.g., slope) of thetrend, a number of instances on which the trend is based, the actionwith which the trend corresponds, and the user with whom the trendcorresponds.

At step 1104, the digital personal assistant is caused to automaticallyschedule a designated time for the user to perform a future instance ofthe action in accordance with the trend, including causing the digitalpersonal assistant to configure a visual representation of a calendar ofthe user to indicate that availability of the user at the designatedtime is tentative or booked. In an example implementation, causationlogic 1210 causes digital personal assistant 1206 to automaticallyschedule the designated time for the user to perform the future instanceof the action in accordance with the trend. Causation logic 1210 maycause digital personal assistant 1206 to automatically schedule thedesignated time in response to receipt of the trend indicator 1214. Forexample, causation logic 1210 may cause digital personal assistant 1206to automatically schedule the designated time based at least in part onthe trend indicator 1214 indicating the trend. In accordance with thisexample, causation logic 1210 may analyze the trend that is indicated bythe trend indicator 1214 to determine the future instance of the actionthat is to be performed by the user. For instance, causation logic 1210may use an extrapolation technique with regard to the instances of theaction, which are analyzed at step 1102 to determine the trend, in orderto determine the future instance of the action that is to be performedby the user. In accordance with this implementation, causation logic1210 causes digital personal assistant 1206 to configure the visualrepresentation of the calendar of the user to indicate that theavailability of the user at the designated time is tentative or booked.

Causation logic 1210 may cause digital personal assistant 1206 toautomatically schedule the designated time for the user to perform thefuture instance of the action in any of a variety of ways. For instance,causation logic 1210 may generate a scheduling instruction 1242 inresponse to the receipt of the trend indicator 1214. The schedulinginstruction 1242 instructs digital personal assistant 1206 to performscheduling operation(s) 1244. The scheduling operation(s) 1244 includeautomatically scheduling the designated time for the user to perform thefuture instance of the action.

In some example embodiments, one or more steps 1102 and/or 1104 offlowchart 1100 may not be performed. Moreover, steps in addition to orin lieu of steps 1102 and/or 1104 may be performed. For instance, in anexample embodiment, the method of flowchart 1100 further includesdetermining an amount of travel time that the user is statisticallylikely to experience during travel to a location at which the futureinstance of the action is to be performed. For example, determinationlogic 1218 may determine the amount of travel time that the user isstatistically likely to experience during travel to the location. Inaccordance with this example, user information 1232 may includeinformation pertaining to travel times of the user. For instance, theuser information 1232 may include historical information that indicatesan amount of travel time that the user previously experienced duringtravel from specified source(s) to specified destination(s). Thehistorical information may indicate an amount of travel time that theuser experienced during historical travels to the location at which theinstance of the action is to be performed. The historical informationmay indicate multiple amounts of time corresponding to the multiplerespective historical travels, an average travel time for the historicaltravels, and/or a median travel time for the historical travels. Theuser information 1232 may include other information that may affect theamount of time (e.g., anticipated traffic congestion at the designatedtime, anticipated weather at the designated time, and/or travel timesexperienced by other users during travel to the location). In furtheraccordance with this example, determination logic 1218 may perform astatistical analysis with regard to the user information 1232 todetermine the amount of travel time that the user is statisticallylikely to experience during travel to the location. Determination logic1218 may generate a travel time indicator 1216 in response todetermining the amount of travel time that the user is statisticallylikely to experience during travel to the location. The travel timeindicator 1216 specifies the amount of travel time that the user isstatistically likely to experience during travel to the location.

In accordance with this embodiment, the method of flowchart 1100 furtherincludes causing the digital personal assistant to configure the visualrepresentation of the calendar of the user to indicate the amount oftravel time. For example, causation logic 1210 may cause digitalpersonal assistant 1206 to configure the visual representation of thecalendar of the user to indicate the amount of travel time. Inaccordance with this example, causation logic 1210 may cause digitalpersonal assistant 1206 to configure the visual representation of thecalendar of the user in response to receipt of the travel time indicator1216. For instance, causation logic 1210 may cause digital personalassistant 1206 to configure the visual representation of the calendar ofthe user to indicate the amount of travel time based at least in part onthe travel time indicator 1216 specifying the amount of travel time.

In accordance with this example, causation logic 1210 may cause digitalpersonal assistant 1206 to access scheduling functionality of a calendarapplication that maintains the calendar of the user. For instance,causation logic 1210 may cause digital personal assistant 1206 to add avisual representation of the travel time (e.g., as an appointment and/ora meeting) in the visual representation of the calendar using thescheduling functionality and/or increase a size of a visualrepresentation of the future instance of the activity in the visualrepresentation of the calendar, for example, by increasing a number oftime increments that the visual representation of the future instance ofthe activity covers in the calendar to account for the travel time.

In another example embodiment, the method of flowchart 1100 furtherincludes inferring an importance of the future instance of the action.For example, inference logic 1212 may infer the importance of the futureinstance of the action. In accordance with this example, inference logic1212 may discover the importance of the future instance of the actionbased on an inference 1224, which indicates the importance. Inferencelogic 1212 may infer the importance of the future instance fromcommunications regarding the action, though the scope of the exampleembodiments is not limited in this respect. Inference logic 1212 maygenerate an importance indicator 1228 in response to inferring theimportance. The importance indicator 1228 may specify the importance ofthe future instance of the action.

In a first aspect of this embodiment, causing the digital personalassistant to automatically schedule the designated time for the user toperform the future instance of the action includes automaticallyreducing an amount of time allocated to a previously scheduled activityto accommodate the future instance of the action based at least in parton an inference that the importance of the future instance of the actionis greater than an importance of the previously scheduled activity. Inaccordance with this aspect, automatically reducing the amount of timeallocated to the previously scheduled activity may include automaticallychanging a representation of the previously scheduled activity on thevisual representation of the calendar to indicate that the amount oftime allocated to the previously scheduled activity is reduced.

In a second aspect of this embodiment, causing the digital personalassistant to automatically schedule the designated time for the user toperform the future instance of the action includes automaticallycancelling a previously scheduled activity to accommodate the futureinstance of the action based at least in part on an inference that theimportance of the future instance of the action is greater than animportance of the previously scheduled activity. In accordance with thisaspect, automatically cancelling a previously scheduled activity toaccommodate the future instance of the action may include automaticallydeleting a representation of the previously scheduled activity from thevisual representation of the calendar to indicate that the previouslyscheduled activity is cancelled.

In a third aspect of this embodiment, causing the digital personalassistant to automatically schedule the designated time for the user toperform the future instance of the action includes causing the digitalpersonal assistant to automatically reschedule and/or automaticallypropose to reschedule a previously scheduled activity to accommodate thefuture instance of the action based at least in part on an inferencethat the importance of the future instance of the action is greater thanan importance of the previously scheduled activity.

In an example of this aspect, causing the digital personal assistant toautomatically reschedule and/or automatically propose to reschedule thepreviously scheduled activity includes causing the digital personalassistant to automatically reschedule the previously scheduled activityto accommodate the future instance of the action. In accordance withthis example, causing the digital personal assistant to automaticallyreschedule the previously scheduled activity to accommodate the futureinstance of the action may include one or more of the steps shown inflowchart 1300 of FIG. 13. Flowchart 1300 may be performed by causationlogic 1210 shown in FIG. 12, for example. For illustrative purposes,flowchart 400 is described with respect to causation logic 500 of FIG.5, which is an example of causation logic 1210, according to anembodiment. Further structural and operational embodiments will beapparent to persons skilled in the relevant art(s) based on thediscussion regarding flowchart 1300.

Before discussing flowchart 1300, it should be mentioned that computingsystem 1200 may not include one or more of intent-based scheduling logic1202, digital personal assistant 1206, analysis logic 1208, causationlogic 1210, inference logic 1212, and/or determination logic 1218.Furthermore, computing system 1200 may include components in addition toor in lieu of intent-based scheduling logic 1202, digital personalassistant 1206, analysis logic 1208, causation logic 1210, inferencelogic 1212, and/or determination logic 1218.

As shown in FIG. 13, the method of flowchart 1300 begins at step 1302.In step 1302, the calendar of the user is automatically analyzed todetermine time(s) at which the user is available to participate in thepreviously scheduled activity. In an example implementation, calendaranalyzer 502 automatically analyzes the calendar of the user todetermine the time(s) at which the user is available to participate inthe previously scheduled activity. In accordance with thisimplementation, calendar analyzer 502 may generate a time indicator 512in response to determining the time(s) at which the user is available toparticipate in the previously scheduled activity. The time indicator 512specifies the time(s) at which the user is available to participate inthe previously scheduled activity.

At step 1304, an inquiry is automatically provided to other user(s) whoare scheduled to participate in the previously scheduled activity. Theinquiry presents at least one time as a possible time at which toparticipate in the previously scheduled activity. In an exampleimplementation, inquiry provider 504 automatically provides an inquiry514 to the other user(s) who are scheduled to participate in thepreviously scheduled activity. The inquiry 514 presents at least onetime as a possible time at which to participate in the previouslyscheduled activity.

At step 1306, a response to the inquiry is received that indicatesselection of a designated time by at least one of the other user(s). Inan example implementation, time changer 506 receives a response 510 tothe inquiry 514 that indicates selection of the designated time by atleast one of the other user(s).

At step 1308, the time at which the previously scheduled activity is tobe performed is changed to the designated time based at least in part onthe response to the inquiry indicating selection of the designated time.In an example implementation, time changer 506 changes the time at whichthe previously scheduled activity is to be performed to the designatedtime based at least in part on the response 510 to the inquiry 514indicating selection of the designated time.

Example illustrations of some of the example techniques described hereinwill not be described. In a first example illustration, a man is talkingwith his family in their living room. The man may say, “Hey, we shouldreally go watch that movie tomorrow.” In response, the man's wife maysay, “Great, we should do that. What time are they playing?” A digitalpersonal assistant may automatically insert the show times on the man'scalendar and/or the woman's calendar and say, “I have some show timesfor you.”

In a second example illustration, a first person says to a secondperson, “Hey, can you update this item.” The second person may say,“Yeah, I'll updated it and send it to you today.” A digital personalassistant may automatically offer to block some time on the secondperson's calendar for updating the item. For instance, the digitalpersonal assistant may say, “Hey, you have an hour free” or “You arebusy this afternoon, but you have an hour free now; you might want tojust do it now.”

In one aspect of this illustration, the digital personal assistant mayreschedule or shorten a duration allotted for a team meeting that thesecond user is scheduled to attend in order to accommodate the seconduser's updating the item. The digital personal assistant may determinethat updating the item is more critical than the team meeting andtherefore may send a notification to the members of the team to informthem that the team meeting has been rescheduled or shortened. Thedigital personal assistant may determine that the team meeting was setup through email. The digital personal assistant may therefore choose tosend the notification to the members through email.

In another aspect of this illustration, the digital personal assistantmay automatically determine alternative times at which the second useris available and send an inquiry to the members of the team to askwhether any of the alternative times are acceptable, considering thatthe team meeting needs to be rescheduled. The digital personal assistantmay automatically reschedule the team meeting upon receiving responsesregarding the alternative times from the members of the team.

Any one or more of intent-based scheduling logic 110, intent-basedscheduling logic 302, analysis logic 308, causation logic 310, inferencelogic 312, topic logic 314, identification logic 316, determinationlogic 318, causation logic 500, calendar analyzer 502, inquiry provider504, time changer 506, intent-based scheduling logic 802, identificationlogic 808, causation logic 810, inference logic 812, topic logic 814,selection logic 816, determination logic 818, attribute logic 820,intent-based scheduling logic 1002, analysis logic 1008, causation logic1010, intent-based scheduling logic 1202, analysis logic 1208, causationlogic 1210, inference logic 1212, determination logic 1218, flowchart200, flowchart 400, flowchart 600, flowchart 700, flowchart 900,flowchart 1100, and/or flowchart 1300 may be implemented in hardware,software, firmware, or any combination thereof.

For example, any one or more of intent-based scheduling logic 110,intent-based scheduling logic 302, analysis logic 308, causation logic310, inference logic 312, topic logic 314, identification logic 316,determination logic 318, causation logic 500, calendar analyzer 502,inquiry provider 504, time changer 506, intent-based scheduling logic802, identification logic 808, causation logic 810, inference logic 812,topic logic 814, selection logic 816, determination logic 818, attributelogic 820, intent-based scheduling logic 1002, analysis logic 1008,causation logic 1010, intent-based scheduling logic 1202, analysis logic1208, causation logic 1210, inference logic 1212, determination logic1218, flowchart 200, flowchart 400, flowchart 600, flowchart 700,flowchart 900, flowchart 1100, and/or flowchart 1300 may be implemented,at least in part, as computer program code configured to be executed inone or more processors.

In another example, any one or more of intent-based scheduling logic110, intent-based scheduling logic 302, analysis logic 308, causationlogic 310, inference logic 312, topic logic 314, identification logic316, determination logic 318, causation logic 500, calendar analyzer502, inquiry provider 504, time changer 506, intent-based schedulinglogic 802, identification logic 808, causation logic 810, inferencelogic 812, topic logic 814, selection logic 816, determination logic818, attribute logic 820, intent-based scheduling logic 1002, analysislogic 1008, causation logic 1010, intent-based scheduling logic 1202,analysis logic 1208, causation logic 1210, inference logic 1212,determination logic 1218, flowchart 200, flowchart 400, flowchart 600,flowchart 700, flowchart 900, flowchart 1100, and/or flowchart 1300 maybe implemented, at least in part, as hardware logic/electricalcircuitry. Such hardware logic/electrical circuitry may include one ormore hardware logic components. Examples of a hardware logic componentinclude but are not limited to a field-programmable gate array (FPGA),an application-specific integrated circuit (ASIC), anapplication-specific standard product (ASSP), a system-on-a-chip system(SoC), a complex programmable logic device (CPLD), etc. For instance, aSoC may include an integrated circuit chip that includes one or more ofa processor (e.g., a microcontroller, microprocessor, digital signalprocessor (DSP), etc.), memory, one or more communication interfaces,and/or further circuits and/or embedded firmware to perform itsfunctions.

III. Further Discussion of Some Example Embodiments

A first example system to perform intent-based scheduling via a digitalpersonal assistant comprises analysis logic configured to analyze one ormore communications from a first user to identify a first communicationfrom the first user that indicates that the first user has an intent tohave a first meeting between at least the first user and one or moresecond users. The analysis logic is further configured to analyze one ormore communications from the one or more second users to identify one ormore second communications from the one or more second users that are inresponse to the first communication and that indicate that the one ormore second users have the intent to have the first meeting. The firstexample system further comprises causation logic configured to cause thedigital personal assistant to at least one of automatically propose orautomatically schedule a time to have the first meeting between at leastthe first user and the one or more second users based at least in parton the first communication and the one or more second communicationsindicating that the first user and the one or more second users have theintent to have the first meeting.

In a first aspect of the first example system, the first example systemfurther comprises inference logic configured to infer an importance ofthe first meeting. In accordance with the first aspect, the causationlogic is configured to cause the digital personal assistant to at leastone of automatically reschedule or automatically propose to reschedule asecond meeting to accommodate the first meeting based at least in parton an inference that the importance of the first meeting is greater thanan importance of the second meeting.

In an example of the first aspect of the first example system, thecausation logic is configured to cause the digital personal assistant toautomatically reschedule the second meeting to accommodate the firstmeeting. In accordance with this example, the causation logic comprisesa calendar analyzer configured to automatically analyze at least onecalendar of at least one respective second user of the one or moresecond users to determine one or more times at which the at least onesecond user is available to have the second meeting. In furtheraccordance with this example, the causation logic further comprises aninquiry provider configured to automatically provide an inquiry to oneor more specified users who are scheduled to attend the second meeting.The inquiry presents at least one time from the one or more times as apossible time at which to conduct the second meeting. In furtheraccordance with this example, the causation logic further comprises atime changer configured to change the time at which the second meetingis to be conducted to a designated time, which is selected from the atleast one time by at least one of the one or more users who arescheduled to attend the second meeting, based at least in part on aresponse to the inquiry indicating selection of the designated time.

In a second aspect of the first example system, the first example systemfurther comprises inference logic configured to infer an importance ofthe first meeting. In accordance with the second aspect, the causationlogic is configured to cause the digital personal assistant toautomatically reduce a duration of a second meeting to accommodate thefirst meeting based at least in part on an inference that the importanceof the first meeting is greater than an importance of the secondmeeting. The second aspect of the first example system may beimplemented in combination with the first aspect of the first examplesystem, though the example embodiments are not limited in this respect.

In a third aspect of the first example system, the first example systemfurther comprises inference logic configured to infer an importance ofthe first meeting. In accordance with the third aspect, the causationlogic is configured to cause the digital personal assistant toautomatically cancel a second meeting to accommodate the first meetingbased at least in part on an inference that the importance of the firstmeeting is greater than an importance of the second meeting. The thirdaspect of the first example system may be implemented in combinationwith the first and/or second aspect of the first example system, thoughthe example embodiments are not limited in this respect.

In a fourth aspect of the first example system, the first example systemfurther comprises topic logic configured to determine a topic of thefirst meeting. In accordance with the fourth aspect, the first examplesystem further comprises identification logic configured to identify athird user who has an attribute that corresponds to the topic. Infurther accordance with the fourth aspect, the causation logic isconfigured to cause the digital personal assistant to suggest that thethird user be invited to the first meeting based at least in part on thethird user having the attribute that corresponds to the topic. Thefourth aspect of the first example system may be implemented incombination with the first, second, and/or third aspect of the firstexample system, though the example embodiments are not limited in thisrespect.

In a fifth aspect of the first example system, the first example systemfurther comprises inference logic configured to infer that a document isrelevant to the first meeting. In accordance with the fifth aspect, thecausation logic is configured to cause the digital personal assistant toattach the document to a calendar entry that represents the firstmeeting based at least in part on an inference that the document isrelevant to the first meeting. The fifth aspect of the first examplesystem may be implemented in combination with the first, second, third,and/or fourth aspect of the first example system, though the exampleembodiments are not limited in this respect.

In a sixth aspect of the first example system, the first example systemfurther comprises inference logic configured to infer a title of thefirst meeting from at least one of (a) at least one of the one or morecommunications from the first user or (b) at least one of the one ormore communications from the one or more second users. The sixth aspectof the first example system may be implemented in combination with thefirst, second, third, fourth, and/or fifth aspect of the first examplesystem, though the example embodiments are not limited in this respect.

In a seventh aspect of the first example system, the first examplesystem further comprises inference logic configured to infer an agendaof the first meeting from at least one of (a) at least one of the one ormore communications from the first user or (b) at least one of the oneor more communications from the one or more second users. The seventhaspect of the first example system may be implemented in combinationwith the first, second, third, fourth, fifth, and/or sixth aspect of thefirst example system, though the example embodiments are not limited inthis respect.

In an eighth aspect of the first example system, the analysis logic isconfigured to automatically generate notes from communications among atleast the first user and the one or more second users that occur duringthe meeting. In accordance with the eighth aspect, the causation logicis configured to cause the digital personal assistant to provide thenotes to at least one of (a) the first user or (b) at least one seconduser of the one or more second users in response to automaticallygenerating the notes. The eighth aspect of the first example system maybe implemented in combination with the first, second, third, fourth,fifth, sixth, and/or seventh aspect of the first example system, thoughthe example embodiments are not limited in this respect.

In a ninth aspect of the first example system, the first example systemfurther comprises determination logic configured to determine that anamount of information that is to be discussed during the first meetingis not capable of being discussed within an amount of time that isallocated for the first meeting. In accordance with the ninth aspect,the causation logic is configured to cause the digital personalassistant to automatically schedule a follow-up meeting for discussionof the information that is not discussed during the first meeting. Theninth aspect of the first example system may be implemented incombination with the first, second, third, fourth, fifth, sixth,seventh, and/or eighth aspect of the first example system, though theexample embodiments are not limited in this respect.

In a tenth aspect of the first example system, the causation logic isconfigured to cause the digital personal assistant to automaticallyschedule the time to have the first meeting. The causation logic isconfigured to cause the digital personal assistant to automaticallyconfigure a visual representation of one or more calendars of the one ormore respective second users to indicate that attendance of the one ormore second users at the meeting is tentative. The tenth aspect of thefirst example system may be implemented in combination with the first,second, third, fourth, fifth, sixth, seventh, eighth, and/or ninthaspect of the first example system, though the example embodiments arenot limited in this respect.

In an eleventh aspect of the first example system, the analysis logic isconfigured to automatically monitor conversations between the first userand one or more other users across a plurality of types of communicationchannels. In accordance with the eleventh aspect, the one or morecommunications from the first user include a plurality of communicationsthat are from the conversations and that are received via the pluralityof types of communication channels. The eleventh aspect of the firstexample system may be implemented in combination with the first, second,third, fourth, fifth, sixth, seventh, eighth, ninth, and/or tenth aspectof the first example system, though the example embodiments are notlimited in this respect.

A second example system to perform intent-based scheduling via a digitalpersonal assistant comprises identification logic configured to identifyinteractions among a plurality of users, the identification logicfurther configured to identify tools that are used to facilitate theinteractions. The second example system further comprises inferencelogic configured to infer an intent to have a meeting between theplurality of users. The second example system further comprisesselection logic configured to automatically select a designated toolfrom the tools to establish communication for the meeting based at leastin part on the designated tool being used more than other tools tofacilitate the interactions. The second example system further comprisescausation logic configured to cause the digital personal assistant to atleast one of automatically schedule the meeting or automatically proposeto schedule the meeting based at least in part on an inference of theintent to have the meeting.

In a first aspect of the second example system, the inference logic isconfigured to infer the intent to have the meeting from a plurality ofcommunications among at least some of the plurality of users.

In a second aspect of the second example system, the second examplesystem further comprises topic logic configured to determine a topic ofthe meeting. In accordance with the second aspect, the second examplesystem further comprises attribute logic configured to determine that atleast one attribute of a designated user that is included in theplurality of users corresponds to the topic. In further accordance withthe second aspect, the causation logic is configured to cause thedigital personal assistant to automatically schedule the meeting, thecausation logic configured to cause the digital personal assistant toautomatically specify that attendance of the designated user at themeeting is required based at least in part on the at least one attributeof the designated user corresponding to the topic. The second aspect ofthe second example system may be implemented in combination with thefirst aspect of the second example system, though the exampleembodiments are not limited in this respect.

In a third aspect of the second example system, the second examplesystem further comprises topic logic configured to determine a topic ofthe meeting. In accordance with the third aspect, the second examplesystem further comprises attribute logic configured to determine that adesignated user does not have at least one attribute that corresponds tothe topic, the designated user included in the plurality of users. Infurther accordance with the third aspect, the causation logic isconfigured to cause the digital personal assistant to automaticallyschedule the meeting, the causation logic configured to case the digitalpersonal assistant to automatically specify that attendance of thedesignated user at the meeting is optional based at least in part on thedesignated user not having at least one attribute that corresponds tothe topic. The third aspect of the second example system may beimplemented in combination with the first and/or second aspect of thesecond example system, though the example embodiments are not limited inthis respect.

In a fourth aspect of the second example system, the second examplesystem further comprises topic logic configured to determine a topic ofthe meeting. In accordance with the fourth aspect, the second examplesystem further comprises attribute logic configured to determine that adesignated user does not have at least one attribute that corresponds tothe topic, the designated user included in the plurality of users. Infurther accordance with the fourth aspect, the causation logic isconfigured to cause the digital personal assistant to automaticallyschedule the meeting, the causation logic configured to cause thedigital personal assistant to not invite the designated user to attendthe meeting based at least in part on the designated user not having atleast one attribute that corresponds to the topic. The fourth aspect ofthe second example system may be implemented in combination with thefirst, second, and/or third aspect of the second example system, thoughthe example embodiments are not limited in this respect.

In a fifth aspect of the second example system, the causation logic isconfigured to cause the digital personal assistant to automaticallyschedule the meeting, the causation logic configured to cause thedigital personal assistant to automatically invite at least a subset ofthe plurality of users to attend the meeting. In accordance with thefifth aspect, the second example system further comprises determinationlogic configured to determine that one or more users in the subsetdecline an invitation to the meeting. In further accordance with thefifth aspect, the inference logic is configured to infer an importanceof each user in the subset to attend the meeting. In further accordancewith the fifth aspect, the causation logic is configured to cause thedigital personal assistant to automatically reschedule the meeting toinclude each user in the subset who has an importance that is greaterthan or equal to a threshold importance and to not include each user inthe subset who has an importance that is less than the thresholdimportance in response to inferring the importance of each user in thesubset, at least one of the one or more users in the subset who declinethe invitation having an importance that is greater than or equal to thethreshold importance. The fifth aspect of the second example system maybe implemented in combination with the first, second, third, and/orfourth aspect of the second example system, though the exampleembodiments are not limited in this respect.

In an example of the fifth aspect of the second example system, thecausation logic is configured to cause the digital personal assistant totake into consideration a time zone of each user in the subset who hasan importance that is greater than or equal to the threshold importanceto establish a time at which the meeting is to occur.

In a sixth aspect of the second example system, the inference logic isconfigured to infer an importance of the meeting to each of theplurality of users. In accordance with the sixth aspect, the causationlogic is configured to cause the digital personal assistant to invite afirst subset of the plurality of users to attend the meeting based atleast in part on the importance of the meeting to each user in the firstsubset reaching a threshold importance and to not invite a second subsetof the plurality of users to attend the meeting based at least in parton the importance of the meeting to each user in the second subset notreaching the threshold importance. The sixth aspect of the secondexample system may be implemented in combination with the first, second,third, fourth, and/or fifth aspect of the second example system, thoughthe example embodiments are not limited in this respect.

In a seventh aspect of the second example system, the identificationlogic is configured to automatically monitor conversations among theplurality of users across a plurality of types of communicationchannels. In accordance with the seventh aspect, the conversationsinclude the interactions, which are received via the plurality of typesof communication channels. The seventh aspect of the second examplesystem may be implemented in combination with the first, second, third,fourth, fifth, and/or sixth aspect of the second example system, thoughthe example embodiments are not limited in this respect.

A third example system to perform intent-based scheduling via a digitalpersonal assistant comprises analysis logic configured to analyze one ormore communications from a first user to infer from at least a firstcommunication of the one or more communications that the first user hasan intent to perform an activity. The third example system furthercomprises causation logic configured to cause the digital personalassistant to automatically schedule a designated time on a visualrepresentation of a calendar of the first user to perform the activityby automatically updating the visual representation of the calendar toinclude a visual representation of the activity that is configured toindicate that the designated time is scheduled to perform the activity,based at least in part on an inference from at least the firstcommunication that the first user has the intent to perform theactivity.

In a first aspect of the third example system, the causation logic isconfigured to cause the digital personal assistant to automaticallyconfigure the visual representation of the calendar of the first user,which is configured for viewing by at least one second user that isdifferent from the first user, to indicate that availability of thefirst user at the designated time is tentative.

In an example of the first aspect of the third example system, thecausation logic is configured to cause the digital personal assistant toautomatically configure a second visual representation of the calendarof the first user, which is configured for viewing by the first user, toindicate that the availability of the first user at the designated timeis free.

In a first implementation of this example, the causation logic isconfigured to cause the digital personal assistant to reconfigure thesecond visual representation of the calendar of the first user to changean indication of the availability of the first user at the designatedtime in the second visual representation from free to booked in responseto receipt of an acceptance of an invitation to perform the activity atthe designated time from the first user and further in response to thedigital personal assistant being caused to automatically schedule thedesignated time on the visual representation of the calendar to performthe activity.

In a second implementation of this example, the causation logic isconfigured to cause the digital personal assistant to reconfigure thevisual representation of the calendar of the first user, which is forviewing by the at least one second user, to change an indication of theavailability of the first user at the designated time in the visualrepresentation from tentative to booked in response to receipt of anacceptance of an invitation to perform the activity at the designatedtime from the first user and further in response to the digital personalassistant being caused to automatically schedule the designated time onthe visual representation of the calendar to perform the activity.

In a second aspect of the third example system, the causation logic isconfigured to cause the digital personal assistant to automaticallyconfigure the visual representation of the calendar of the first user,which is configured for viewing by the first user and not for viewing byone or more second users, to indicate that availability of the firstuser at the designated time is tentative or booked. In accordance withthe second aspect, the causation logic is configured to cause thedigital personal assistant to automatically configure a second visualrepresentation of the calendar of the first user, which is configuredfor viewing by the one or more second users, to indicate that theavailability of the first user at the designated time is free. Thesecond aspect of the third example system may be implemented incombination with the first aspect of the third example system, thoughthe example embodiments are not limited in this respect.

In a first example of the second aspect of the third example system, thecausation logic is configured to cause the digital personal assistant toreconfigure the second visual representation of the calendar of thefirst user to change an indication of the availability of the first userat the designated time in the second visual representation from free tobooked in response to receipt of an acceptance of an invitation toperform the activity at the designated time from the first user andfurther in response to the digital personal assistant being caused toautomatically schedule the designated time on the visual representationof the calendar to perform the activity.

In a second example of the second aspect of the third example system,the causation logic is configured to cause the digital personalassistant to reconfigure the visual representation of the calendar ofthe first user, which is configured for viewing by the first user andnot for viewing by the one or more second users, to change an indicationof the availability of the first user at the designated time in thevisual representation from tentative to booked in response to receipt ofan acceptance of an invitation to perform the activity at the designatedtime from the first user and further in response to the digital personalassistant being caused to automatically schedule the designated time onthe visual representation of the calendar to perform the activity.

In a third aspect of the third example system, the analysis logic isfurther configured to analyze one or more communications from a seconduser to identify an inquiry from the second user as to whether the firstperson is to perform the activity. In accordance with the third aspect,the analysis logic is configured to infer that the first user has theintent to perform the activity from at least the first communication inresponse to identification of the inquiry. The third aspect of the thirdexample system may be implemented in combination with the first and/orsecond aspect of the third example system, though the exampleembodiments are not limited in this respect.

In a fourth aspect of the third example system, the analysis logic isconfigured to infer an importance of the activity from at least one ofthe one or more communications. In accordance with the fourth aspect,the causation logic is configured to automatically reschedule a secondactivity that is represented on the calendar to accommodate the activitybased at least in part on the importance of the activity that isinferred from the at least one of the one or more communications beinggreater than an importance of the second activity. The fourth aspect ofthe third example system may be implemented in combination with thefirst, second, and/or third aspect of the third example system, thoughthe example embodiments are not limited in this respect.

In a fifth aspect of the third example system, the analysis logic isconfigured to infer an importance of the activity from at least one ofthe one or more communications. In accordance with the fifth aspect, thecausation logic is configured to automatically reduce a duration of asecond activity that is represented on the calendar to accommodate theactivity based at least in part on the importance of the activity thatis inferred from the at least one of the one or more communicationsbeing greater than an importance of the second activity. The fifthaspect of the third example system may be implemented in combinationwith the first, second, third, and/or fourth aspect of the third examplesystem, though the example embodiments are not limited in this respect.

In a sixth aspect of the third example system, the analysis logic isconfigured to infer an importance of the activity from at least one ofthe one or more communications. In accordance with the sixth aspect, thecausation logic is configured to automatically cancel a second activityto accommodate the activity based at least in part on the importance ofthe activity that is inferred from the at least one of the one or morecommunications being greater than an importance of the second activity.The sixth aspect of the third example system may be implemented incombination with the first, second, third, fourth, and/or fifth aspectof the third example system, though the example embodiments are notlimited in this respect.

In a seventh aspect of the third example system, the analysis logic isconfigured to automatically monitor conversations between the first userand one or more other users across a plurality of types of communicationchannels. In accordance with the seventh aspect, the one or morecommunications from the first user include a plurality of communicationsthat are from the conversations and that are received via the pluralityof types of communication channels. The seventh aspect of the thirdexample system may be implemented in combination with the first, second,third, fourth, fifth, and/or sixth aspect of the third example system,though the example embodiments are not limited in this respect.

A fourth example system to perform intent-based scheduling via a digitalpersonal assistant comprises analysis logic configured to analyze aplurality of instances of an action that are performed by a user at aplurality of respective historical time instances to identify a trendwith regard to the plurality of instances of the action. The fourthexample system further comprises causation logic configured to cause thedigital personal assistant to automatically schedule a designated timefor the user to perform a future instance of the action in accordancewith the trend by configuring a visual representation of a calendar ofthe user to indicate that availability of the user at the designatedtime is tentative or booked.

In a first aspect of the fourth example system, the fourth examplesystem further comprises determination logic configured to determine anamount of travel time that the user is statistically likely toexperience during travel to a location at which the future instance ofthe action is to be performed. In accordance with the first aspect, thecausation logic is configured to cause the digital personal assistant toconfigure the visual representation of the calendar of the user toindicate the amount of travel time.

In a second aspect of the fourth example system, the fourth examplesystem further comprises inference logic configured to infer animportance of the future instance of the action. In accordance with thesecond aspect, the causation logic is configured to cause the digitalpersonal assistant to at least one of automatically reschedule orautomatically propose to reschedule a previously scheduled activity toaccommodate the future instance of the action based at least in part onan inference that the importance of the future instance of the action isgreater than an importance of the previously scheduled activity. Thesecond aspect of the fourth example system may be implemented incombination with the first aspect of the fourth example system, thoughthe example embodiments are not limited in this respect.

In an example of the second aspect of the fourth example system, thecausation logic is configured to cause the digital personal assistant toautomatically reschedule the previously scheduled activity toaccommodate the future instance of the action. In accordance with thisexample, the causation logic further comprises a calendar analyzerconfigured to automatically analyze the calendar of the user todetermine one or more times at which the user is available toparticipate in the previously scheduled activity. In further accordancewith this example, the causation logic further comprises an inquiryprovider configured to automatically provide an inquiry to one or moreother users who are scheduled to participate in the previously scheduledactivity. The inquiry presents at least one time from the one or moretimes as a possible time at which to participate in the previouslyscheduled activity. In further accordance with this example, thecausation logic further comprises changing the time at which thepreviously scheduled activity is to be performed to a designated time,which is selected from the at least one time by at least one of the oneor more other users, based at least in part on a response to the inquiryindicating selection of the designated time.

In a third aspect of the fourth example system, the fourth examplesystem further comprises inference logic configured to infer animportance of the future instance of the action. In accordance with thethird aspect, the causation logic is configured to automatically reducean amount of time allocated to a previously scheduled activity toaccommodate the future instance of the action based at least in part onan inference that the importance of the future instance of the action isgreater than an importance of the previously scheduled activity. Thethird aspect of the fourth example system may be implemented incombination with the first and/or second aspect of the fourth examplesystem, though the example embodiments are not limited in this respect.

In a fourth aspect of the fourth example system, the fourth examplesystem further comprises inference logic configured to infer animportance of the future instance of the action. In accordance with thefourth aspect, the causation logic is configured to automatically cancela previously scheduled activity to accommodate the future instance ofthe action based at least in part on an inference that the importance ofthe future instance of the action is greater than an importance of thepreviously scheduled activity. The fourth aspect of the fourth examplesystem may be implemented in combination with the first, second, and/orthird aspect of the fourth example system, though the exampleembodiments are not limited in this respect.

In a first example method of performing intent-based scheduling via adigital personal assistant, one or more communications from a first userare analyzed to identify a first communication from the first user thatindicates that the first user has an intent to have a first meetingbetween at least the first user and one or more second users. One ormore communications from the one or more second users are analyzed toidentify one or more second communications from the one or more secondusers that are in response to the first communication and that indicatethat the one or more second users have the intent to have the firstmeeting. The digital personal assistant is caused to at least one ofautomatically propose or automatically schedule a time to have the firstmeeting between at least the first user and the one or more second usersbased at least in part on the first communication and the one or moresecond communications indicating that the first user and the one or moresecond users have the intent to have the first meeting.

In a first aspect of the first example method, an importance of thefirst meeting is inferred. In accordance with the first aspect, causingthe digital personal assistant to at least one of automatically proposeor automatically schedule the time to have the first meeting comprisescausing the digital personal assistant to at least one of automaticallyreschedule or automatically propose to reschedule a second meeting toaccommodate the first meeting based at least in part on an inferencethat the importance of the first meeting is greater than an importanceof the second meeting.

In an example of the first aspect of the first example method, causingthe digital personal assistant to at least one of automaticallyreschedule or automatically propose to reschedule the second meetingcomprises causing the digital personal assistant to automaticallyreschedule the second meeting to accommodate the first meeting. Inaccordance with this example, causing the digital personal assistant toautomatically reschedule the second meeting comprises automaticallyanalyzing at least one calendar of at least one respective second userof the one or more second users to determine one or more times at whichthe at least one second user is available to have the second meeting. Infurther accordance with this example, causing the digital personalassistant to automatically reschedule the second meeting furthercomprises automatically providing an inquiry to one or more specifiedusers who are scheduled to attend the second meeting, the inquirypresenting at least one time from the one or more times as a possibletime at which to conduct the second meeting. In further accordance withthis example, causing the digital personal assistant to automaticallyreschedule the second meeting further comprises receiving a response tothe inquiry that indicates selection of a designated time from the atleast one time by at least one of the one or more users who arescheduled to attend the second meeting. In further accordance with thisexample, causing the digital personal assistant to automaticallyreschedule the second meeting further comprises changing the time atwhich the second meeting is to be conducted to the designated time basedat least in part on the response to the inquiry indicating selection ofthe designated time.

In a second aspect of the first example method, the first example methodfurther comprises inferring an importance of the first meeting. Inaccordance with the second aspect, causing the digital personalassistant to at least one of automatically propose or automaticallyschedule the time to have the first meeting comprises causing thedigital personal assistant to automatically reduce a duration of asecond meeting to accommodate the first meeting based at least in parton an inference that the importance of the first meeting is greater thanan importance of the second meeting. The second aspect of the firstexample method may be implemented in combination with the first aspectof the first example method, though the example embodiments are notlimited in this respect.

In a third aspect of the first example method, the first example methodfurther comprises inferring an importance of the first meeting. Inaccordance with the third aspect, causing the digital personal assistantto at least one of automatically propose or automatically schedule thetime to have the first meeting comprises causing the digital personalassistant to automatically cancel a second meeting to accommodate thefirst meeting based at least in part on an inference that the importanceof the first meeting is greater than an importance of the secondmeeting. The third aspect of the first example method may be implementedin combination with the first and/or second aspect of the first examplemethod, though the example embodiments are not limited in this respect.

In a fourth aspect of the first example method, the first example methodfurther comprises determining a topic of the first meeting. Inaccordance with the fourth aspect, the first example method furthercomprises identifying a third user who has an attribute that correspondsto the topic. In further accordance with the fourth aspect, the firstexample method further comprises causing the digital personal assistantto suggest that the third user be invited to the first meeting based atleast in part on the third user having the attribute that corresponds tothe topic. The fourth aspect of the first example method may beimplemented in combination with the first, second, and/or third aspectof the first example method, though the example embodiments are notlimited in this respect.

In a fifth aspect of the first example method, the first example methodfurther comprises inferring that a document is relevant to the firstmeeting. In accordance with the fifth aspect, the first example methodfurther comprises causing the digital personal assistant to attach thedocument to a calendar entry that represents the first meeting based atleast in part on an inference that the document is relevant to the firstmeeting. The fifth aspect of the first example method may be implementedin combination with the first, second, third, and/or fourth aspect ofthe first example method, though the example embodiments are not limitedin this respect.

In a sixth aspect of the first example method, the first example methodfurther comprises inferring a title of the first meeting from at leastone of (a) at least one of the one or more communications from the firstuser or (b) at least one of the one or more communications from the oneor more second users. The sixth aspect of the first example method maybe implemented in combination with the first, second, third, fourth,and/or fifth aspect of the first example method, though the exampleembodiments are not limited in this respect.

In a seventh aspect of the first example method, the first examplemethod further comprises inferring an agenda of the first meeting fromat least one of (a) at least one of the one or more communications fromthe first user or (b) at least one of the one or more communicationsfrom the one or more second users. The seventh aspect of the firstexample method may be implemented in combination with the first, second,third, fourth, fifth, and/or sixth aspect of the first example method,though the example embodiments are not limited in this respect.

In an eighth aspect of the first example method, the first examplemethod further comprises automatically generating notes fromcommunications among at least the first user and the one or more secondusers that occur during the meeting. In accordance with the eighthaspect, the first example method further comprises causing the digitalpersonal assistant to provide the notes to at least one of (a) the firstuser or (b) at least one second user of the one or more second users inresponse to automatically generating the notes. The eighth aspect of thefirst example method may be implemented in combination with the first,second, third, fourth, fifth, sixth, and/or seventh aspect of the firstexample method, though the example embodiments are not limited in thisrespect.

In ninth aspect of the first example method, the first example methodfurther comprises determining that an amount of information that is tobe discussed during the first meeting is not capable of being discussedwithin an amount of time that is allocated for the first meeting. Inaccordance with the ninth aspect, the first example method furthercomprises causing the digital personal assistant to automaticallyschedule a follow-up meeting for discussion of the information that isnot discussed during the first meeting. The ninth aspect of the firstexample method may be implemented in combination with the first, second,third, fourth, fifth, sixth, seventh, and/or eighth aspect of the firstexample method, though the example embodiments are not limited in thisrespect.

In tenth aspect of the first example method, causing the digitalpersonal assistant to at least one of automatically propose orautomatically schedule the time to have the first meeting comprisescausing the digital personal assistant to automatically schedule thetime to have the first meeting, including causing the digital personalassistant to automatically configure a visual representation of one ormore calendars of the one or more respective second users to indicatethat attendance of the one or more second users at the meeting istentative. The tenth aspect of the first example method may beimplemented in combination with the first, second, third, fourth, fifth,sixth, seventh, eighth, and/or ninth aspect of the first example method,though the example embodiments are not limited in this respect.

In eleventh aspect of the first example method, the first example methodfurther comprises automatically monitoring conversations between thefirst user and one or more other users across a plurality of types ofcommunication channels. In accordance with the eleventh aspect,analyzing the one or more communications from the first user comprisesanalyzing the one or more communications from the first user, whichinclude a plurality of communications that are from the conversationsand that are received via the plurality of types of communicationchannels. The eleventh aspect of the first example method may beimplemented in combination with the first, second, third, fourth, fifth,sixth, seventh, eighth, ninth, and/or tenth aspect of the first examplemethod, though the example embodiments are not limited in this respect.

In a second example method of performing intent-based scheduling via adigital personal assistant, interactions among a plurality of users areidentified. Tools that are used to facilitate the interactions areidentified. An intent to have a meeting between the plurality of usersis inferred. A designated tool is automatically selected from the toolsto establish communication for the meeting based at least in part on thedesignated tool being used more than other tools to facilitate theinteractions. The digital personal assistant is caused to at least oneof automatically schedule the meeting or automatically propose toschedule the meeting based at least in part on an inference of theintent to have the meeting.

In a first aspect of the second example method, inferring the intentcomprises inferring the intent to have the meeting from a plurality ofcommunications among at least some of the plurality of users.

In a second aspect of the second example method, the second examplemethod further comprises determining a topic of the meeting. Inaccordance with the second aspect, the second example method furthercomprises determining that at least one attribute of a designated userthat is included in the plurality of users corresponds to the topic. Infurther accordance with the second aspect, causing the digital personalassistant to at least one of automatically schedule the meeting orautomatically propose to schedule the meeting comprises causing thedigital personal assistant to automatically schedule the meeting,including causing the digital personal assistant to automaticallyspecify that attendance of the designated user at the meeting isrequired based at least in part on the at least one attribute of thedesignated user corresponding to the topic. The second aspect of thesecond example method may be implemented in combination with the firstaspect of the second example method, though the example embodiments arenot limited in this respect.

In a third aspect of the second example method, the second examplemethod further comprises determining a topic of the meeting. Inaccordance with the third aspect, the second example method furthercomprises determining that a designated user does not have at least oneattribute that corresponds to the topic. The designated user is includedin the plurality of users. In further accordance with the third aspect,causing the digital personal assistant to at least one of automaticallyschedule the meeting or automatically propose to schedule the meetingcomprises causing the digital personal assistant to automaticallyschedule the meeting, including causing the digital personal assistantto automatically specify that attendance of the designated user at themeeting is optional based at least in part on the designated user nothaving at least one attribute that corresponds to the topic. The thirdaspect of the second example method may be implemented in combinationwith the first and/or second aspect of the second example method, thoughthe example embodiments are not limited in this respect.

In a fourth aspect of the second example method, the second examplemethod further comprises determining a topic of the meeting. Inaccordance with the fourth aspect, the second example method furthercomprises determining that a designated user does not have at least oneattribute that corresponds to the topic. The designated user is includedin the plurality of users. In further accordance with the fourth aspect,causing the digital personal assistant to at least one of automaticallyschedule the meeting or automatically propose to schedule the meetingcomprises causing the digital personal assistant to automaticallyschedule the meeting, including causing the digital personal assistantto not invite the designated user to attend the meeting based at leastin part on the designated user not having at least one attribute thatcorresponds to the topic. The fourth aspect of the second example methodmay be implemented in combination with the first, second, and/or thirdaspect of the second example method, though the example embodiments arenot limited in this respect.

In a fifth aspect of the second example method, causing the digitalpersonal assistant to at least one of automatically schedule the meetingor automatically propose to schedule the meeting comprises causing thedigital personal assistant to automatically schedule the meeting,including causing the digital personal assistant to automatically inviteat least a subset of the plurality of users to attend the meeting. Inaccordance with the fifth aspect, the second example method furthercomprises determining that one or more users in the subset decline aninvitation to the meeting. In further accordance with the fifth aspect,the second example method further comprises inferring an importance ofeach user in the subset to attend the meeting. In further accordancewith the fifth aspect, the second example method further comprisescausing the digital personal assistant to automatically reschedule themeeting to include each user in the subset who has an importance that isgreater than or equal to a threshold importance and to not include eachuser in the subset who has an importance that is less than the thresholdimportance in response to inferring the importance of each user in thesubset, at least one of the one or more users in the subset who declinethe invitation having an importance that is greater than or equal to thethreshold importance. The fifth aspect of the second example method maybe implemented in combination with the first, second, third, and/orfourth aspect of the second example method, though the exampleembodiments are not limited in this respect.

In a sixth aspect of the second example method, causing the digitalpersonal assistant to automatically reschedule the meeting comprisescausing the digital personal assistant to take into consideration a timezone of each user in the subset who has an importance that is greaterthan or equal to the threshold importance to establish a time at whichthe meeting is to occur. The sixth aspect of the second example methodmay be implemented in combination with the first, second, third, fourth,and/or fifth aspect of the second example method, though the exampleembodiments are not limited in this respect.

In a seventh aspect of the second example method, the second examplemethod further comprises inferring an importance of the meeting to eachof the plurality of users. In accordance with the seventh aspect,causing the digital personal assistant to at least one of automaticallyschedule the meeting or automatically propose to schedule the meetingcomprises causing the digital personal assistant to invite a firstsubset of the plurality of users to attend the meeting based at least inpart on the importance of the meeting to each user in the first subsetreaching a threshold importance and to not invite a second subset of theplurality of users to attend the meeting based at least in part on theimportance of the meeting to each user in the second subset not reachingthe threshold importance. The seventh aspect of the second examplemethod may be implemented in combination with the first, second, third,fourth, fifth, and/or sixth aspect of the second example method, thoughthe example embodiments are not limited in this respect.

In an eighth aspect of the second example method, the second examplemethod further comprises automatically monitoring conversations amongthe plurality of users across a plurality of types of communicationchannels. In accordance with the eighth aspect, identifying theinteractions comprises identifying the interactions that are included inthe conversations and that are received via the plurality of types ofcommunication channels. The eighth aspect of the second example methodmay be implemented in combination with the first, second, third, fourth,fifth, sixth, and/or seventh aspect of the second example method, thoughthe example embodiments are not limited in this respect.

In a third example method of performing intent-based scheduling via adigital personal assistant, one or more communications from a first userare analyzed to infer from at least a first communication of the one ormore communications that the first user has an intent to perform anactivity. The digital personal assistant is caused to automaticallyschedule a designated time on a visual representation of a calendar ofthe first user to perform the activity, including causing the digitalpersonal assistant to automatically update the visual representation ofthe calendar to include a visual representation of the activity that isconfigured to indicate that the designated time is scheduled to performthe activity, based at least in part on an inference from at least thefirst communication that the first user has the intent to perform theactivity.

In a first aspect of the third example method, causing the digitalpersonal assistant to automatically schedule the designated timecomprises causing the digital personal assistant to automaticallyconfigure the visual representation of the calendar of the first user,which is configured for viewing by at least one second user that isdifferent from the first user, to indicate that availability of thefirst user at the designated time is tentative.

In an example of the first aspect of the third example method, causingthe digital personal assistant to automatically schedule the designatedtime further comprises causing the digital personal assistant toautomatically configure a second visual representation of the calendarof the first user, which is configured for viewing by the first user, toindicate that the availability of the first user at the designated timeis free.

In a first implementation of this example, the third example methodfurther comprises receiving an acceptance of an invitation to performthe activity at the designated time from the first user in response tocausing the digital personal assistant to automatically schedule thedesignated time on the visual representation of the calendar to performthe activity. In accordance with the first implementation, the thirdexample method further comprises causing the digital personal assistantto reconfigure the second visual representation of the calendar of thefirst user to change an indication of the availability of the first userat the designated time in the second visual representation from free tobooked in response to receiving the acceptance of the invitation.

In a second implementation of this example, the third example methodfurther comprises receiving an acceptance of an invitation to performthe activity at the designated time from the first user in response tocausing the digital personal assistant to automatically schedule thedesignated time on the visual representation of the calendar to performthe activity. In accordance with the second implementation, the thirdexample method further comprises causing the digital personal assistantto reconfigure the visual representation of the calendar of the firstuser, which is for viewing by the at least one second user, to change anindication of the availability of the first user at the designated timein the visual representation from tentative to booked in response toreceiving the acceptance of the invitation.

In a second aspect of the third example method, causing the digitalpersonal assistant to automatically schedule the designated timecomprises causing the digital personal assistant to automaticallyconfigure the visual representation of the calendar of the first user,which is configured for viewing by the first user and not for viewing byone or more second users, to indicate that availability of the firstuser at the designated time is tentative or booked. In accordance withthe second aspect, causing the digital personal assistant toautomatically schedule the designated time further comprises causing thedigital personal assistant to automatically configure a second visualrepresentation of the calendar of the first user, which is configuredfor viewing by the one or more second users, to indicate that theavailability of the first user at the designated time is free. Thesecond aspect of the third example method may be implemented incombination with the first aspect of the third example method, thoughthe example embodiments are not limited in this respect.

In a first example of the second aspect of the third example method, thethird example method further comprises receiving an acceptance of aninvitation to perform the activity at the designated time from the firstuser in response to causing the digital personal assistant toautomatically schedule the designated time on the visual representationof the calendar to perform the activity. In accordance with the firstexample, the third example method further comprises causing the digitalpersonal assistant to reconfigure the second visual representation ofthe calendar of the first user to change an indication of theavailability of the first user at the designated time in the secondvisual representation from free to booked in response to receiving theacceptance of the invitation.

In a second example of the second aspect of the third example method,the third example method further comprises receiving an acceptance of aninvitation to perform the activity at the designated time from the firstuser in response to causing the digital personal assistant toautomatically schedule the designated time on the visual representationof the calendar to perform the activity. In accordance with the secondexample, the third example method further comprises causing the digitalpersonal assistant to reconfigure the visual representation of thecalendar of the first user, which is configured for viewing by the firstuser and not for viewing by the one or more second users, to change anindication of the availability of the first user at the designated timein the visual representation from tentative to booked in response toreceiving the acceptance of the invitation.

In a third aspect of the third example method, the third example methodfurther comprises analyzing one or more communications from a seconduser to identify an inquiry from the second user as to whether the firstperson is to perform the activity. In accordance with the third aspect,the first user having the intent to perform the activity is inferredfrom at least the first communication in response to the inquiry beingidentified. The third aspect of the third example method may beimplemented in combination with the first and/or second aspect of thethird example method, though the example embodiments are not limited inthis respect.

In a fourth aspect of the third example method, the third example methodfurther comprises inferring an importance of the activity from at leastone of the one or more communications. In accordance with the fourthaspect, causing the digital personal assistant to automatically schedulethe designated time on the visual representation of the calendar of thefirst user comprises automatically rescheduling a second activity thatis represented on the calendar to accommodate the activity based atleast in part on the importance of the activity that is inferred fromthe at least one of the one or more communications being greater than animportance of the second activity. The fourth aspect of the thirdexample method may be implemented in combination with the first, second,and/or third aspect of the third example method, though the exampleembodiments are not limited in this respect.

In a fifth aspect of the third example method, the third example methodfurther comprises inferring an importance of the activity from at leastone of the one or more communications. In accordance with the fifthaspect, causing the digital personal assistant to automatically schedulethe designated time on the visual representation of the calendar of thefirst user comprises automatically reducing a duration of a secondactivity that is represented on the calendar to accommodate the activitybased at least in part on the importance of the activity that isinferred from the at least one of the one or more communications beinggreater than an importance of the second activity. The fifth aspect ofthe third example method may be implemented in combination with thefirst, second, third, and/or fourth aspect of the third example method,though the example embodiments are not limited in this respect.

In a sixth aspect of the third example method, the third example methodfurther comprises inferring an importance of the activity from at leastone of the one or more communications. In accordance with the sixthaspect, causing the digital personal assistant to automatically schedulethe designated time on the visual representation of the calendar of thefirst user comprises automatically cancelling a second activity toaccommodate the activity based at least in part on the importance of theactivity that is inferred from the at least one of the one or morecommunications being greater than an importance of the second activity.The sixth aspect of the third example method may be implemented incombination with the first, second, third, fourth, and/or fifth aspectof the third example method, though the example embodiments are notlimited in this respect.

In a seventh aspect of the third example method, the third examplemethod further comprises automatically monitoring conversations betweenthe first user and one or more other users across a plurality of typesof communication channels. In accordance with the seventh aspect,analyzing the one or more communications from the first user comprisesanalyzing the one or more communications from the first user, whichinclude a plurality of communications that are from the conversationsand that are received via the plurality of types of communicationchannels. The seventh aspect of the third example method may beimplemented in combination with the first, second, third, fourth, fifth,and/or sixth aspect of the third example method, though the exampleembodiments are not limited in this respect.

In a fourth example method of performing intent-based scheduling via adigital personal assistant, a plurality of instances of an action thatare performed by a user at a plurality of respective historical timeinstances is analyzed to identify a trend with regard to the pluralityof instances of the action. The digital personal assistant is caused toautomatically schedule a designated time for the user to perform afuture instance of the action in accordance with the trend, includingcausing the digital personal assistant to configure a visualrepresentation of a calendar of the user to indicate that availabilityof the user at the designated time is tentative or booked.

In a first aspect of the fourth example method, the fourth examplemethod further comprises determining an amount of travel time that theuser is statistically likely to experience during travel to a locationat which the future instance of the action is to be performed. Inaccordance with the first aspect, the fourth example method furthercomprises causing the digital personal assistant to configure the visualrepresentation of the calendar of the user to indicate the amount oftravel time.

In a second aspect of the fourth example method, the fourth examplemethod further comprises inferring an importance of the future instanceof the action. In accordance with the second aspect, causing the digitalpersonal assistant to automatically schedule the designated time for theuser to perform the future instance of the action comprises causing thedigital personal assistant to at least one of automatically rescheduleor automatically propose to reschedule a previously scheduled activityto accommodate the future instance of the action based at least in parton an inference that the importance of the future instance of the actionis greater than an importance of the previously scheduled activity. Thesecond aspect of the fourth example method may be implemented incombination with the first aspect of the fourth example method, thoughthe example embodiments are not limited in this respect.

In an example of the second aspect of the fourth example method, causingthe digital personal assistant to at least one of automaticallyreschedule or automatically propose to reschedule the previouslyscheduled activity comprises causing the digital personal assistant toautomatically reschedule the previously scheduled activity toaccommodate the future instance of the action. In accordance with thethird aspect, causing the digital personal assistant to automaticallyreschedule the previously scheduled activity to accommodate the futureinstance of the action comprises automatically analyzing the calendar ofthe user to determine one or more times at which the user is availableto participate in the previously scheduled activity. In furtheraccordance with the third aspect, causing the digital personal assistantto automatically reschedule the previously scheduled activity toaccommodate the future instance of the action further comprisesautomatically providing an inquiry to one or more other users who arescheduled to participate in the previously scheduled activity, theinquiry presenting at least one time from the one or more times as apossible time at which to participate in the previously scheduledactivity. In further accordance with the third aspect, causing thedigital personal assistant to automatically reschedule the previouslyscheduled activity to accommodate the future instance of the actionfurther comprises receiving a response to the inquiry that indicatesselection of a designated time from the at least one time by at leastone of the one or more other users. In further accordance with the thirdaspect, causing the digital personal assistant to automaticallyreschedule the previously scheduled activity to accommodate the futureinstance of the action further comprises changing the time at which thepreviously scheduled activity is to be performed to the designated timebased at least in part on the response to the inquiry indicatingselection of the designated time.

In a third aspect of the fourth example method, the fourth examplemethod further comprises inferring an importance of the future instanceof the action. In accordance with the third aspect, causing the digitalpersonal assistant to automatically schedule the designated time for theuser to perform the future instance of the action comprisesautomatically reducing an amount of time allocated to a previouslyscheduled activity to accommodate the future instance of the actionbased at least in part on an inference that the importance of the futureinstance of the action is greater than an importance of the previouslyscheduled activity. The third aspect of the fourth example method may beimplemented in combination with the first and/or second aspect of thefourth example method, though the example embodiments are not limited inthis respect.

In a fourth aspect of the fourth example method, the fourth examplemethod further comprises inferring an importance of the future instanceof the action. In accordance with the fourth aspect, causing the digitalpersonal assistant to automatically schedule the designated time for theuser to perform the future instance of the action comprisesautomatically cancelling a previously scheduled activity to accommodatethe future instance of the action based at least in part on an inferencethat the importance of the future instance of the action is greater thanan importance of the previously scheduled activity. The fourth aspect ofthe fourth example method may be implemented in combination with thefirst, second, and/or third aspect of the fourth example method, thoughthe example embodiments are not limited in this respect.

A first example computer program product comprises a computer-readablestorage medium having instructions recorded thereon for enabling aprocessor-based system to perform intent-based scheduling via a digitalpersonal assistant. The instructions comprise first instructions forenabling the processor-based system to analyze one or morecommunications from a first user to identify a first communication fromthe first user that indicates that the first user has an intent to havea first meeting between at least the first user and one or more secondusers. The first instructions comprise instructions for enabling theprocessor-based system to analyze one or more communications from theone or more second users to identify one or more second communicationsfrom the one or more second users that are in response to the firstcommunication and that indicate that the one or more second users havethe intent to have the first meeting. The instructions further comprisesecond instructions for enabling the processor-based system to cause thedigital personal assistant to at least one of automatically propose orautomatically schedule a time to have the first meeting between at leastthe first user and the one or more second users based at least in parton the first communication and the one or more second communicationsindicating that the first user and the one or more second users have theintent to have the first meeting.

A second example computer program product comprises a computer-readablestorage medium having instructions recorded thereon for enabling aprocessor-based system to perform intent-based scheduling via a digitalpersonal assistant. The instructions comprise first instructions forenabling the processor-based system to identify interactions among aplurality of users and to identify tools that are used to facilitate theinteractions. The instructions further comprise second instructions forenabling the processor-based system to infer an intent to have a meetingbetween the plurality of users. The instructions further comprise thirdinstructions for enabling the processor-based system to automaticallyselect a designated tool from the tools to establish communication forthe meeting based at least in part on the designated tool being usedmore than other tools to facilitate the interactions. The instructionsfurther comprise fourth instructions for enabling the processor-basedsystem to cause the digital personal assistant to at least one ofautomatically schedule the meeting or automatically propose to schedulethe meeting based at least in part on an inference of the intent to havethe meeting.

A third example computer program product comprises a computer-readablestorage medium having instructions recorded thereon for enabling aprocessor-based system to perform intent-based scheduling via a digitalpersonal assistant. The instructions comprise first instructions forenabling the processor-based system to analyze one or morecommunications from a first user to infer from at least a firstcommunication of the one or more communications that the first user hasan intent to perform an activity. The instructions further comprisesecond instructions for enabling the processor-based system to cause thedigital personal assistant to automatically schedule a designated timeon a visual representation of a calendar of the first user to performthe activity by automatically updating the visual representation of thecalendar to include a visual representation of the activity that isconfigured to indicate that the designated time is scheduled to performthe activity, based at least in part on an inference from at least thefirst communication that the first user has the intent to perform theactivity.

A fourth example computer program product comprises a computer-readablestorage medium having instructions recorded thereon for enabling aprocessor-based system to perform intent-based scheduling via a digitalpersonal assistant. The instructions comprise first instructions forenabling the processor-based system to analyze a plurality of instancesof an action that are performed by a user at a plurality of respectivehistorical time instances to identify a trend with regard to theplurality of instances of the action. The instructions further comprisesecond instructions for enabling the processor-based system to cause thedigital personal assistant to automatically schedule a designated timefor the user to perform a future instance of the action in accordancewith the trend by configuring a visual representation of a calendar ofthe user to indicate that availability of the user at the designatedtime is tentative or booked.

IV. Example Computer System

FIG. 14 depicts an example computer 1400 in which embodiments may beimplemented. For instance, any one or more of user devices 102A-102Mand/or any one or more of servers 106A-106N shown in FIG. 1, computingsystem 300 shown in FIG. 3, computing system 800 shown in FIG. 8,computing system 1000 shown in FIG. 10, and/or computing system 1200shown in FIG. 12 may be implemented using computer 1400, including oneor more features of computer 1400 and/or alternative features. Computer1400 may be a general-purpose computing device in the form of aconventional personal computer, a mobile computer, or a workstation, forexample, or computer 1400 may be a special purpose computing device. Thedescription of computer 1400 provided herein is provided for purposes ofillustration, and is not intended to be limiting. Embodiments may beimplemented in further types of computer systems, as would be known topersons skilled in the relevant art(s).

As shown in FIG. 14, computer 1400 includes a processing unit 1402, asystem memory 1404, and a bus 1406 that couples various systemcomponents including system memory 1404 to processing unit 1402. Bus1406 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. System memory 1404 includes read onlymemory (ROM) 1408 and random access memory (RAM) 1410. A basicinput/output system 1412 (BIOS) is stored in ROM 1408.

Computer 1400 also has one or more of the following drives: a hard diskdrive 1414 for reading from and writing to a hard disk, a magnetic diskdrive 1416 for reading from or writing to a removable magnetic disk1418, and an optical disk drive 1420 for reading from or writing to aremovable optical disk 1422 such as a CD ROM, DVD ROM, or other opticalmedia. Hard disk drive 1414, magnetic disk drive 1416, and optical diskdrive 1420 are connected to bus 1406 by a hard disk drive interface1424, a magnetic disk drive interface 1426, and an optical driveinterface 1428, respectively. The drives and their associatedcomputer-readable storage media provide nonvolatile storage ofcomputer-readable instructions, data structures, program modules andother data for the computer. Although a hard disk, a removable magneticdisk and a removable optical disk are described, other types ofcomputer-readable storage media can be used to store data, such as flashmemory cards, digital video disks, random access memories (RAMs), readonly memories (ROM), and the like.

A number of program modules may be stored on the hard disk, magneticdisk, optical disk, ROM, or RAM. These programs include an operatingsystem 1430, one or more application programs 1432, other programmodules 1434, and program data 1436. Application programs 1432 orprogram modules 1434 may include, for example, computer program logicfor implementing any one or more of digital personal assistants108A-108M, intent-based scheduling logic 110, intent-based schedulinglogic 302, digital personal assistant 306, analysis logic 308, causationlogic 310, inference logic 312, topic logic 314, identification logic316, determination logic 318, causation logic 500, calendar analyzer502, inquiry provider 504, time changer 506, intent-based schedulinglogic 802, digital personal assistant 806, identification logic 808,causation logic 810, inference logic 812, topic logic 814, selectionlogic 816, determination logic 818, attribute logic 820, intent-basedscheduling logic 1002, digital personal assistant 1006, analysis logic1008, causation logic 1010, intent-based scheduling logic 1202, digitalpersonal assistant 1206, analysis logic 1208, causation logic 1210,inference logic 1212, determination logic 1218, flowchart 200 (includingany step of flowchart 200), flowchart 400 (including any step offlowchart 400), flowchart 600 (including any step of flowchart 600),flowchart 700 (including any step of flowchart 700), flowchart 900(including any step of flowchart 900), flowchart 1100 (including anystep of flowchart 1100), and/or flowchart 1300 (including any step offlowchart 1300), as described herein.

A user may enter commands and information into the computer 1400 throughinput devices such as keyboard 1438 and pointing device 1440. Otherinput devices (not shown) may include a microphone, joystick, game pad,satellite dish, scanner, touch screen, camera, accelerometer, gyroscope,or the like. These and other input devices are often connected to theprocessing unit 1402 through a serial port interface 1442 that iscoupled to bus 1406, but may be connected by other interfaces, such as aparallel port, game port, or a universal serial bus (USB).

A display device 1444 (e.g., a monitor) is also connected to bus 1406via an interface, such as a video adapter 1446. In addition to displaydevice 1444, computer 1400 may include other peripheral output devices(not shown) such as speakers and printers.

Computer 1400 is connected to a network 1448 (e.g., the Internet)through a network interface or adapter 1450, a modem 1452, or othermeans for establishing communications over the network. Modem 1452,which may be internal or external, is connected to bus 1406 via serialport interface 1442.

As used herein, the terms “computer program medium” and“computer-readable storage medium” are used to generally refer to media(e.g., non-transitory media) such as the hard disk associated with harddisk drive 1414, removable magnetic disk 1418, removable optical disk1422, as well as other media such as flash memory cards, digital videodisks, random access memories (RAMs), read only memories (ROM), and thelike. Such computer-readable storage media are distinguished from andnon-overlapping with communication media (do not include communicationmedia). Communication media embodies computer-readable instructions,data structures, program modules or other data in a modulated datasignal such as a carrier wave. The term “modulated data signal” means asignal that has one or more of its characteristics set or changed insuch a manner as to encode information in the signal. By way of example,and not limitation, communication media includes wireless media such asacoustic, RF, infrared and other wireless media, as well as wired media.Example embodiments are also directed to such communication media.

As noted above, computer programs and modules (including applicationprograms 1432 and other program modules 1434) may be stored on the harddisk, magnetic disk, optical disk, ROM, or RAM. Such computer programsmay also be received via network interface 1450 or serial port interface1442. Such computer programs, when executed or loaded by an application,enable computer 1400 to implement features of embodiments discussedherein. Accordingly, such computer programs represent controllers of thecomputer 1400.

Example embodiments are also directed to computer program productscomprising software (e.g., computer-readable instructions) stored on anycomputer-useable medium. Such software, when executed in one or moredata processing devices, causes data processing device(s) to operate asdescribed herein. Embodiments may employ any computer-useable orcomputer-readable medium, known now or in the future. Examples ofcomputer-readable mediums include, but are not limited to storagedevices such as RAM, hard drives, floppy disks, CD ROMs, DVD ROMs, zipdisks, tapes, magnetic storage devices, optical storage devices,MEMS-based storage devices, nanotechnology-based storage devices, andthe like.

It will be recognized that the disclosed technologies are not limited toany particular computer or type of hardware. Certain details of suitablecomputers and hardware are well known and need not be set forth indetail in this disclosure.

V. Conclusion

Although the subject matter has been described in language specific tostructural features and/or acts, it is to be understood that the subjectmatter defined in the appended claims is not necessarily limited to thespecific features or acts described above. Rather, the specific featuresand acts described above are disclosed as examples of implementing theclaims, and other equivalent features and acts are intended to be withinthe scope of the claims.

What is claimed is:
 1. A system to perform intent-based scheduling via adigital personal assistant, the system comprising: memory; and one ormore processors coupled to the memory, the one or more processorsconfigured to: analyze one or more communications from a first user in aconversation between the first user and one or more second users toidentify a first communication from the first user that indicates thatthe first user has an intent to have a first meeting between at leastthe first user and the one or more second users; analyze one or morecommunications from the one or more second users in the conversationbetween the first user and the one or more second users to identify oneor more second communications from the one or more second users that arein response to the first communication and that indicate that the one ormore second users have the intent to have the first meeting; infer animportance of the first meeting based at least in part on at least oneof the following: a frequency of interaction between the first user andat least one of the one or more second users; a number of interactionsbetween the first user and at least one of the one or more second users;an amount of time that the first user and at least one of the one ormore second users spend together; a number of projects that the firstuser has with at least one of the one or more second users; an amount oftime at least one of (a) the first user or (b) at least one of the oneor more second users devotes to subject matter that is to be discussedat the first meeting; or an extent of knowledge that at least one of (a)the first user or (b) at least one of the one or more second users hasregarding subject matter of the first meeting; and cause the digitalpersonal assistant to at least one of: automatically schedule a time ona first calendar of the first user and one or more second calendars ofthe one or more respective second users to have the first meetingbetween at least the first user and the one or more second users, orautomatically propose the time such that acceptance of the time causesthe digital personal assistant to automatically schedule the time on thefirst calendar of the first user and the one or more second calendars ofthe one or more respective second users to have the first meeting, basedat least in part on an inference of the importance of the first meetingand further based at least in part on the first communication and theone or more second communications in the conversation between the firstuser and the one or more second users indicating that the first user andthe one or more second users have the intent to have the first meeting.2. The system of claim 1, wherein the one or more processors areconfigured to: cause the digital personal assistant to at least one ofautomatically reschedule or automatically propose to reschedule a secondmeeting to accommodate the first meeting based at least in part on aninference that the importance of the first meeting is greater than animportance of the second meeting.
 3. The system of claim 2, wherein theone or more processors are configured to: cause the digital personalassistant to automatically reschedule the second meeting to accommodatethe first meeting; automatically analyze at least one calendar of atleast one respective second user of the one or more second users todetermine one or more times at which the at least one second user isavailable to have the second meeting; automatically provide an inquiryto one or more specified users who are scheduled to attend the secondmeeting, the inquiry presenting at least one time from the one or moretimes as a possible time at which to conduct the second meeting; andchange the time at which the second meeting is to be conducted to adesignated time, which is selected from the at least one time by atleast one of the one or more users who are scheduled to attend thesecond meeting, based at least in part on a response to the inquiryindicating selection of the designated time.
 4. The system of claim 1,wherein the one or more processors are configured to: cause the digitalpersonal assistant to automatically reduce a duration of a secondmeeting to accommodate the first meeting based at least in part on aninference that the importance of the first meeting is greater than animportance of the second meeting.
 5. The system of claim 1, wherein theone or more processors are configured to: cause the digital personalassistant to automatically cancel a second meeting to accommodate thefirst meeting based at least in part on an inference that the importanceof the first meeting is greater than an importance of the secondmeeting.
 6. The system of claim 1, wherein the one or more processorsare configured to: determine a topic of the first meeting; identify athird user who has an attribute that corresponds to the topic; and causethe digital personal assistant to suggest that the third user be invitedto the first meeting based at least in part on the third user having theattribute that corresponds to the topic.
 7. The system of claim 1,wherein the one or more processors are configured to: infer that adocument is relevant to the first meeting; and cause the digitalpersonal assistant to attach the document to a calendar entry thatrepresents the first meeting based at least in part on an inference thatthe document is relevant to the first meeting.
 8. The system of claim 1,wherein the one or more processors are configured to: infer a title ofthe first meeting, as a result of monitoring the conversation, from atleast one of (a) at least one of the one or more communications from thefirst user in the conversation between the first user and the one ormore second users or (b) at least one of the one or more communicationsfrom the one or more second users in the conversation between the firstuser and the one or more second users.
 9. The system of claim 1, whereinthe one or more processors are configured to: infer an agenda of thefirst meeting, as a result of monitoring the conversation, from at leastone of (a) at least one of the one or more communications from the firstuser in the conversation between the first user and the one or moresecond users or (b) at least one of the one or more communications fromthe one or more second users in the conversation between the first userand the one or more second users.
 10. The system of claim 1, wherein theone or more processors are configured to: automatically generate notesfrom communications among at least the first user and the one or moresecond users that occur during the meeting; and cause the digitalpersonal assistant to provide the notes to at least one of (a) the firstuser or (b) at least one second user of the one or more second users inresponse to automatically generating the notes.
 11. The system of claim1, wherein the one or more processors are configured to: determine thatan amount of information that is to be discussed subsequently during thefirst meeting is not capable of being discussed within an amount of timethat is allocated for the first meeting; and cause the digital personalassistant to automatically schedule a follow-up meeting for discussionof the information that is not discussed during the first meeting. 12.The system of claim 1, wherein the one or more processors are configuredto: cause the digital personal assistant to automatically schedule thetime to have the first meeting; and cause the digital personal assistantto automatically configure a visual representation of the one or moresecond calendars of the one or more respective second users to indicatethat attendance of the one or more second users at the meeting at theautomatically scheduled time is tentative.
 13. The system of claim 1,wherein the one or more processors are configured to automaticallymonitor conversations between the first user and one or more other usersacross a plurality of types of communication channels; and wherein theone or more communications from the first user include a plurality ofcommunications that are from the conversations and that are received viathe plurality of types of communication channels.
 14. A system toperform intent-based scheduling via a digital personal assistant, thesystem comprising: memory; and one or more processors coupled to thememory, the one or more processors configured to: identify interactionsamong a plurality of users; identify a plurality of tools that are usedto facilitate the interactions, including identify one or more toolsthat are used to facilitate each of the interactions, based at least inpart on receipt of interaction information that specifies the one ormore tools that are used to facilitate each of the interactions;generate tool information that specifies the tools that are used tofacilitate the interactions in response to receipt of the interactioninformation; infer an intent to have a meeting between the plurality ofusers; automatically select a designated tool from the plurality oftools to establish communication for the meeting in response to receiptof the tool information based at least in part on an analysis of thetool information indicating that the designated tool is used more thanother tools to facilitate the interactions among the plurality of users;and cause the digital personal assistant to at least one ofautomatically schedule the meeting or automatically propose to schedulethe meeting based at least in part on an inference of the intent to havethe meeting.
 15. The system of claim 14, wherein the one or moreprocessors are configured to infer the intent to have the meeting from aplurality of communications among at least some of the plurality ofusers.
 16. The system of claim 14, wherein the one or more processorsare configured to: determine a topic of the meeting; determine that atleast one attribute of a designated user that is included in theplurality of users corresponds to the topic; cause the digital personalassistant to automatically schedule the meeting; and cause the digitalpersonal assistant to automatically specify that attendance of thedesignated user at the meeting is required based at least in part on theat least one attribute of the designated user corresponding to thetopic.
 17. The system of claim 14, wherein the one or more processorsare configured to: determine a topic of the meeting; determine that adesignated user does not have at least one attribute that corresponds tothe topic, the designated user included in the plurality of users; causethe digital personal assistant to automatically schedule the meeting;and cause the digital personal assistant to automatically specify thatattendance of the designated user at the meeting is optional based atleast in part on the designated user not having at least one attributethat corresponds to the topic.
 18. The system of claim 14, wherein theone or more processors are configured to: determine a topic of themeeting; determine that a designated user does not have at least oneattribute that corresponds to the topic, the designated user included inthe plurality of users; cause the digital personal assistant toautomatically schedule the meeting; and cause the digital personalassistant to not invite the designated user to attend the meeting basedat least in part on the designated user not having at least oneattribute that corresponds to the topic.
 19. The system of claim 14,wherein the one or more processors are configured to: cause the digitalpersonal assistant to automatically schedule the meeting; cause thedigital personal assistant to automatically invite at least a subset ofthe plurality of users to attend the meeting; determine that one or moreusers in the subset decline an invitation to the meeting; infer animportance of each user in the subset to attend the meeting; and causethe digital personal assistant to automatically reschedule the meetingto include each user in the subset who has an importance that is greaterthan or equal to a threshold importance and to not include each user inthe subset who has an importance that is less than the thresholdimportance in response to inferring the importance of each user in thesubset, at least one of the one or more users in the subset who declinethe invitation having an importance that is greater than or equal to thethreshold importance.
 20. The system of claim 19, wherein the one ormore processors are configured to cause the digital personal assistantto take into consideration a time zone of each user in the subset whohas an importance that is greater than or equal to the thresholdimportance to establish a time at which the meeting is to occur.
 21. Thesystem of claim 14, wherein the one or more processors are configuredto: infer an importance of the meeting to each of the plurality ofusers; and cause the digital personal assistant to invite a first subsetof the plurality of users to attend the meeting based at least in parton the importance of the meeting to each user in the first subsetreaching a threshold importance and to not invite a second subset of theplurality of users to attend the meeting based at least in part on theimportance of the meeting to each user in the second subset not reachingthe threshold importance.
 22. The system of claim 14, wherein the one ormore processors are configured to automatically monitor conversationsamong the plurality of users across a plurality of types ofcommunication channels; and wherein the conversations include theinteractions, which are received via the plurality of types ofcommunication channels.
 23. A method of performing intent-basedscheduling via a digital personal assistant using one or more processorsof a processor-based system, the method comprising: analyzing one ormore communications from a first user in a conversation between thefirst user and one or more second users, using at least one of the oneor more processors, to identify a first communication from the firstuser that indicates that the first user has an intent to have a firstmeeting between at least the first user and one or more second users;analyzing one or more communications from the one or more second usersin the conversation between the first user and the one or more secondusers, using at least one of the one or more processors, to identify oneor more second communications from the one or more second users that arein response to the first communication and that indicate that the one ormore second users have the intent to have the first meeting; causing thedigital personal assistant to at least one of: automatically schedule atime on a first calendar of the first user and one or more secondcalendars of the one or more respective second users to have the firstmeeting between at least the first user and the one or more secondusers, or automatically propose the time such that acceptance of thetime causes the digital personal assistant to automatically schedule thetime on the first calendar of the first user and the one or more secondcalendars of the one or more respective second users to have the firstmeeting, based at least in part on the first communication and the oneor more second communications in the conversation between the first userand the one or more second users indicating that the first user and theone or more second users have the intent to have the first meeting;inferring an importance of the first meeting; and causing the digitalpersonal assistant to automatically reduce a duration of a secondmeeting to accommodate the first meeting based at least in part on aninference that the importance of the first meeting is greater than animportance of the second meeting.